Title: | Manipulate MCMC Samples |
Version: | 0.6.2 |
Description: | Functions and classes to store, manipulate and summarise Monte Carlo Markov Chain (MCMC) samples. For more information see Brooks et al. (2011) <isbn:978-1-4200-7941-8>. |
License: | MIT + file LICENSE |
URL: | https://github.com/poissonconsulting/mcmcr, https://poissonconsulting.github.io/mcmcr/ |
BugReports: | https://github.com/poissonconsulting/mcmcr/issues |
Depends: | R (≥ 4.0) |
Imports: | abind, chk, coda, extras, generics, lifecycle, nlist, purrr, stats, term, tibble, universals, utils |
Suggests: | covr, graphics, rlang, testthat (≥ 3.0.0), withr |
RdMacros: | lifecycle |
Config/Needs/website: | poissonconsulting/poissontemplate |
Config/testthat/edition: | 3 |
Encoding: | UTF-8 |
Language: | en-US |
LazyData: | true |
RoxygenNote: | 7.3.2.9000 |
NeedsCompilation: | no |
Packaged: | 2025-01-23 16:04:47 UTC; joe |
Author: | Joe Thorley |
Maintainer: | Joe Thorley <joe@poissonconsulting.ca> |
Repository: | CRAN |
Date/Publication: | 2025-01-23 16:50:01 UTC |
mcmcr: Manipulate MCMC Samples
Description
Functions and classes to store, manipulate and summarise Monte Carlo Markov Chain (MCMC) samples. For more information see Brooks et al. (2011) <isbn:978-1-4200-7941-8>.
Author(s)
Maintainer: Joe Thorley joe@poissonconsulting.ca (ORCID)
Other contributors:
Kirill Müller (ORCID) [contributor]
Nadine Hussein (ORCID) [contributor]
Ayla Pearson (ORCID) [contributor]
Poisson Consulting [copyright holder, funder]
See Also
Useful links:
Report bugs at https://github.com/poissonconsulting/mcmcr/issues
Coerce to an mcarray object
Description
Coerces MCMC objects to an mcarray object.
Usage
as.mcarray(x, ...)
## S3 method for class 'list'
as.mcmcr(x, ...)
Arguments
x |
object to coerce. |
... |
Unused. |
Functions
-
as.mcmcr(list)
: Convert a list of uniquely named objects that can be coerced to[mcmcarray-object]s
to an mcmcr object
See Also
Other coerce:
as.mcmcarray()
,
as.mcmcr()
,
mcmcrs()
Examples
as.mcarray(mcmcr_example$beta)
Markov Chain Monte Carlo Objects
Description
The function mcmc
is used to create a Markov Chain Monte Carlo
object. The input data are taken to be a vector, or a matrix with
one column per variable.
If the optional arguments start
, end
, and thin
are omitted then the chain is assumed to start with iteration 1 and
have thinning interval 1. If data
represents a chain that
starts at a later iteration, the first iteration in the chain should
be given as the start
argument. Likewise, if data
represents a chain that has already been thinned, the thinning
interval should be given as the thin
argument.
An mcmc object may be summarized by the summary
function
and visualized with the plot
function.
MCMC objects resemble time series (ts
) objects and have
methods for the generic functions time
, start
,
end
, frequency
and window
.
Usage
## S3 method for class 'mcarray'
as.mcmc(x, ...)
Arguments
x |
An object that may be coerced to an mcmc object |
... |
Further arguments to be passed to specific methods |
Note
The format of the mcmc class has changed between coda version 0.3
and 0.4. Older mcmc objects will now cause is.mcmc
to
fail with an appropriate warning message. Obsolete mcmc objects can
be upgraded with the mcmcUpgrade
function.
Author(s)
Martyn Plummer
See Also
mcmc.list
,
mcmcUpgrade
,
thin
,
window.mcmc
,
summary.mcmc
,
plot.mcmc
.
Markov Chain Monte Carlo Objects
Description
The function mcmc
is used to create a Markov Chain Monte Carlo
object. The input data are taken to be a vector, or a matrix with
one column per variable.
If the optional arguments start
, end
, and thin
are omitted then the chain is assumed to start with iteration 1 and
have thinning interval 1. If data
represents a chain that
starts at a later iteration, the first iteration in the chain should
be given as the start
argument. Likewise, if data
represents a chain that has already been thinned, the thinning
interval should be given as the thin
argument.
An mcmc object may be summarized by the summary
function
and visualized with the plot
function.
MCMC objects resemble time series (ts
) objects and have
methods for the generic functions time
, start
,
end
, frequency
and window
.
Usage
## S3 method for class 'mcmc'
as.mcmc(x, ...)
Arguments
x |
An object that may be coerced to an mcmc object |
... |
Further arguments to be passed to specific methods |
Note
The format of the mcmc class has changed between coda version 0.3
and 0.4. Older mcmc objects will now cause is.mcmc
to
fail with an appropriate warning message. Obsolete mcmc objects can
be upgraded with the mcmcUpgrade
function.
Author(s)
Martyn Plummer
See Also
mcmc.list
,
mcmcUpgrade
,
thin
,
window.mcmc
,
summary.mcmc
,
plot.mcmc
.
Markov Chain Monte Carlo Objects
Description
The function mcmc
is used to create a Markov Chain Monte Carlo
object. The input data are taken to be a vector, or a matrix with
one column per variable.
If the optional arguments start
, end
, and thin
are omitted then the chain is assumed to start with iteration 1 and
have thinning interval 1. If data
represents a chain that
starts at a later iteration, the first iteration in the chain should
be given as the start
argument. Likewise, if data
represents a chain that has already been thinned, the thinning
interval should be given as the thin
argument.
An mcmc object may be summarized by the summary
function
and visualized with the plot
function.
MCMC objects resemble time series (ts
) objects and have
methods for the generic functions time
, start
,
end
, frequency
and window
.
Usage
## S3 method for class 'mcmcarray'
as.mcmc(x, ...)
Arguments
x |
An object that may be coerced to an mcmc object |
... |
Further arguments to be passed to specific methods |
Note
The format of the mcmc class has changed between coda version 0.3
and 0.4. Older mcmc objects will now cause is.mcmc
to
fail with an appropriate warning message. Obsolete mcmc objects can
be upgraded with the mcmcUpgrade
function.
Author(s)
Martyn Plummer
See Also
mcmc.list
,
mcmcUpgrade
,
thin
,
window.mcmc
,
summary.mcmc
,
plot.mcmc
.
Markov Chain Monte Carlo Objects
Description
The function mcmc
is used to create a Markov Chain Monte Carlo
object. The input data are taken to be a vector, or a matrix with
one column per variable.
If the optional arguments start
, end
, and thin
are omitted then the chain is assumed to start with iteration 1 and
have thinning interval 1. If data
represents a chain that
starts at a later iteration, the first iteration in the chain should
be given as the start
argument. Likewise, if data
represents a chain that has already been thinned, the thinning
interval should be given as the thin
argument.
An mcmc object may be summarized by the summary
function
and visualized with the plot
function.
MCMC objects resemble time series (ts
) objects and have
methods for the generic functions time
, start
,
end
, frequency
and window
.
Usage
## S3 method for class 'mcmcr'
as.mcmc(x, ...)
Arguments
x |
An object that may be coerced to an mcmc object |
... |
Further arguments to be passed to specific methods |
Note
The format of the mcmc class has changed between coda version 0.3
and 0.4. Older mcmc objects will now cause is.mcmc
to
fail with an appropriate warning message. Obsolete mcmc objects can
be upgraded with the mcmcUpgrade
function.
Author(s)
Martyn Plummer
See Also
mcmc.list
,
mcmcUpgrade
,
thin
,
window.mcmc
,
summary.mcmc
,
plot.mcmc
.
Number of Chains
Description
Gets the number of chains of an MCMC object.
Usage
## S3 method for class 'nlists'
as.mcmc(x, ...)
Arguments
x |
An object. |
... |
Other arguments passed to methods. |
Value
An integer scalar of the number of chains.
See Also
Other MCMC dimensions:
niters()
,
npars()
,
nsams()
,
nsims()
,
nterms()
Coerce to an mcmcarray object
Description
Coerces MCMC objects to an mcmcarray-object()
.
Usage
as.mcmcarray(x, ...)
Arguments
x |
object to coerce. |
... |
Unused. |
See Also
Other coerce:
as.mcarray()
,
as.mcmcr()
,
mcmcrs()
Examples
as.mcmcarray(as.mcarray(mcmcr_example$beta))
Convert to an mcmcr object
Description
Converts an MCMC object to an mcmcr-object()
.
Usage
as.mcmcr(x, ...)
## S3 method for class 'mcarray'
as.mcmcr(x, name = "par", ...)
## S3 method for class 'mcmcarray'
as.mcmcr(x, name = "par", ...)
## S3 method for class 'nlist'
as.mcmcr(x, ...)
## S3 method for class 'nlists'
as.mcmcr(x, ...)
## S3 method for class 'mcmc'
as.mcmcr(x, ...)
## S3 method for class 'mcmc.list'
as.mcmcr(x, ...)
## S3 method for class 'mcmcrs'
as.mcmcr(x, ...)
Arguments
x |
An MCMC object. |
... |
Unused. |
name |
A string specifying the parameter name. |
Value
An mcmcr object.
Methods (by class)
-
as.mcmcr(mcarray)
: Convert an mcarray object to an mcmcr object -
as.mcmcr(mcmcarray)
: Convert anmcmcarray-object()
to an mcmcr object -
as.mcmcr(nlist)
: Convert annlist::nlist-object()
to an mcmcr object -
as.mcmcr(nlists)
: Convert annlist::nlists-object()
to an mcmcr object -
as.mcmcr(mcmc)
: Convert ancoda::mcmc()
object to an mcmcr object -
as.mcmcr(mcmc.list)
: Convert ancoda::mcmc.list()
object to an mcmcr object -
as.mcmcr(mcmcrs)
: Convert tanmcmcrs-object()
to an mcmcr object
See Also
Other coerce:
as.mcarray()
,
as.mcmcarray()
,
mcmcrs()
Examples
mcmc.list <- coda::as.mcmc.list(mcmcr::mcmcr_example)
as.mcmcr(mcmc.list)
Convert to an mcmcrs object
Description
Converts an MCMC object to an mcmcrs-object()
.
Usage
as.mcmcrs(x, ...)
## S3 method for class 'list'
as.mcmcrs(x, ...)
## S3 method for class 'mcmcr'
as.mcmcrs(x, name = "mcmcr1", ...)
Arguments
x |
An MCMC object. |
... |
Unused. |
name |
A string specifying the element name. |
Value
An mcmcrs object.
Methods (by class)
-
as.mcmcrs(list)
: Convert a list of[mcmcr-object]s
to an mcmcrs object -
as.mcmcrs(mcmcr)
: Convert anmcmcr-object()
to an mcmcrs object
Examples
as.mcmcrs(mcmcr::mcmcr_example)
Coerce to nlist
Description
Coerce an R object to an nlist_object()
.
Usage
## S3 method for class 'mcmcr'
as_nlist(x, ...)
Arguments
x |
An object. |
... |
Unused. |
Value
An nlist object.
Methods (by class)
-
as_nlist(numeric)
: Coerce named numeric vector to nlist -
as_nlist(list)
: Coerce list to nlist -
as_nlist(data.frame)
: Coerce data.frame to nlist -
as_nlist(mcmc)
: Coerce mcmc (with one iteration) to nlist -
as_nlist(mcmc.list)
: Coerce mcmc.list (with one iteration) to nlist
See Also
Other coerce:
as_nlists()
Examples
as_nlist(list(x = 1:4))
as_nlist(c(`a[2]` = 3, `a[1]` = 2))
Coerce to nlists
Description
Coerce an R object to an nlists_object()
.
Usage
## S3 method for class 'mcmcr'
as_nlists(x, ...)
Arguments
x |
An object. |
... |
Unused. |
Value
An nlists object.
Methods (by class)
-
as_nlists(list)
: Coerce list to nlists -
as_nlists(mcmc)
: Coerce mcmc to nlists -
as_nlists(mcmc.list)
: Coerce mcmc.list to nlists -
as_nlists(nlist)
: Coerce nlist to nlists
See Also
Other coerce:
as_nlist()
Examples
as_nlists(list(nlist(x = c(1, 5)), nlist(x = c(2, 3)), nlist(x = c(3, 2))))
Bind by Chains.
Description
Binds two MCMC objects (with the same parameters and iterations) by chains.
Usage
## S3 method for class 'mcarray'
bind_chains(x, x2, ...)
Arguments
x |
An object. |
x2 |
A second object. |
... |
Other arguments passed to methods. |
Value
The combined object.
See Also
Other MCMC manipulations:
bind_iterations()
,
collapse_chains()
,
estimates()
,
split_chains()
Bind by Chains.
Description
Binds two MCMC objects (with the same parameters and iterations) by chains.
Usage
## S3 method for class 'mcmc'
bind_chains(x, x2, ...)
Arguments
x |
An object. |
x2 |
A second object. |
... |
Other arguments passed to methods. |
Value
The combined object.
See Also
Other MCMC manipulations:
bind_iterations()
,
collapse_chains()
,
estimates()
,
split_chains()
Bind by Chains.
Description
Binds two MCMC objects (with the same parameters and iterations) by chains.
Usage
## S3 method for class 'mcmc.list'
bind_chains(x, x2, ...)
Arguments
x |
An object. |
x2 |
A second object. |
... |
Other arguments passed to methods. |
Value
The combined object.
See Also
Other MCMC manipulations:
bind_iterations()
,
collapse_chains()
,
estimates()
,
split_chains()
Bind by Chains.
Description
Binds two MCMC objects (with the same parameters and iterations) by chains.
Usage
## S3 method for class 'mcmcarray'
bind_chains(x, x2, ...)
Arguments
x |
An object. |
x2 |
A second object. |
... |
Other arguments passed to methods. |
Value
The combined object.
See Also
Other MCMC manipulations:
bind_iterations()
,
collapse_chains()
,
estimates()
,
split_chains()
Bind by Chains.
Description
Binds two MCMC objects (with the same parameters and iterations) by chains.
Usage
## S3 method for class 'mcmcr'
bind_chains(x, x2, ...)
Arguments
x |
An object. |
x2 |
A second object. |
... |
Other arguments passed to methods. |
Value
The combined object.
See Also
Other MCMC manipulations:
bind_iterations()
,
collapse_chains()
,
estimates()
,
split_chains()
Combine two MCMC objects by dimensions
Description
Combines multiple MCMC objects (with the same parameters, chains and iterations) by parameter dimensions.
Usage
bind_dimensions(x, x2, along = NULL, ...)
Arguments
x |
An MCMC object. |
x2 |
a second MCMC object. |
along |
A count (or NULL) indicating the parameter dimension to bind along. |
... |
Unused. |
See Also
Other bind:
bind_dimensions_n()
,
bind_parameters()
Examples
bind_dimensions(mcmcr_example, mcmcr_example)
Combine multiple MCMC objects by parameter dimensions
Description
Combines multiple MCMC objects (with the same parameters, chains and iterations) by parameter dimensions.
Usage
bind_dimensions_n(...)
Arguments
... |
one or more MCMC objects |
See Also
Other bind:
bind_dimensions()
,
bind_parameters()
Examples
bind_dimensions_n(mcmcr_example, mcmcr_example, mcmcr_example)
Combine two MCMC object by parameters
Description
Combines two MCMC objects (with the same chains and iterations) by their parameters.
Usage
bind_parameters(x, x2, ...)
Arguments
x |
an MCMC object |
x2 |
a second MCMC object. |
... |
Unused. |
See Also
Other bind:
bind_dimensions()
,
bind_dimensions_n()
Examples
bind_parameters(
subset(mcmcr_example, pars = "sigma"),
subset(mcmcr_example, pars = "beta")
)
Check mcmcarray
![[Deprecated]](./figures/lifecycle-deprecated.svg)
Description
Usage
check_mcmcarray(x, x_name = substitute(x), error = TRUE)
Arguments
x |
The object to check. |
x_name |
A string of the name of the object. |
error |
A flag indicating whether to throw an informative error or immediately generate an informative message if the check fails. |
Value
An invisible copy of x (it if doesn't throw an error).
See Also
Examples
check_mcmcarray(mcmcr::mcmcr_example$beta)
Check mcmcr
![[Deprecated]](./figures/lifecycle-deprecated.svg)
Description
Usage
check_mcmcr(x, sorted = FALSE, x_name = substitute(x), error = TRUE)
Arguments
x |
The object to check. |
sorted |
A flag specifying whether the parameters must be sorted. |
x_name |
A string of the name of the object. |
error |
A flag indicating whether to throw an informative error or immediately generate an informative message if the check fails. |
Value
An invisible copy of x (it if doesn't throw an error).
See Also
Examples
check_mcmcr(mcmcr::mcmcr_example)
Check MCMC objects
Description
Checks class and structure of MCMC objects.
chk_mcmcarray
checks if mcmcarray-object()
object using
is.array(x) && is.numeric(x)
chk_mcmcr
checks if an mcmcr-object()
.
chk_mcmcrs
checks if an mcmcrs-object()
.
Usage
chk_mcmcarray(x, x_name = NULL)
chk_mcmcr(x, x_name = NULL)
chk_mcmcrs(x, x_name = NULL)
Arguments
x |
The object to check. |
x_name |
A string of the name of object x or NULL. |
Details
To just check class use chk::chk_s3_class()
.
Value
NULL
, invisibly. Called for the side effect of throwing an error
if the condition is not met.
Functions
-
chk_mcmcarray()
: Check mcmcarray Object -
chk_mcmcr()
: Check mcmcr Object -
chk_mcmcrs()
: Check mcmcrs Object
See Also
Examples
# chk_mcmcarray
try(chk_mcmcarray(1))
# chk_mcmcr
chk_mcmcr(as.mcmcr(list(x = 1)))
try(chk_mcmcr(1))
# chk_mcmcrs
chk_mcmcrs(as.mcmcrs(as.mcmcr(list(x = 1))))
try(chk_mcmcrs(1))
Term coefficients
Description
Gets coefficients for all the terms in an MCMC object.
Usage
## S3 method for class 'mcmc'
coef(object, conf_level = 0.95, estimate = median, simplify = TRUE, ...)
Arguments
object |
The MCMC object to get the coefficients for |
conf_level |
A number specifying the confidence level. By default 0.95. |
estimate |
The function to use to calculate the estimate. |
simplify |
A flag specifying whether to return just the estimate, lower, upper and svalue. |
... |
Unused. |
Value
An data frame of the coefficients with the columns indicating the
term
, estimate
,
lower
and upper
credible intervals and svalue
Methods (by class)
-
coef(mcmc)
: Get coefficients for terms in mcmc object
See Also
Examples
coef(mcmcr_example)
Collapse Chains
Description
Collapses an MCMC object's chains into a single chain.
Usage
## S3 method for class 'mcmcr'
collapse_chains(x, ...)
Arguments
x |
An object. |
... |
Other arguments passed to methods. |
Value
The modified object with one chain.
See Also
Other MCMC manipulations:
bind_chains()
,
bind_iterations()
,
estimates()
,
split_chains()
Combine samples by dimensions
Description
Combines MCMC object samples by dimensions along along
using fun
.
Usage
combine_dimensions(x, fun = mean, along = NULL, ...)
Arguments
x |
An MCMC object |
fun |
The function to use when combining dimensions |
along |
A positive integer (or NULL) indicating the parameter dimension(s) to bind along. |
... |
Unused. |
Value
The MCMC object with reduced dimensions.
See Also
Other combine:
combine_samples()
,
combine_samples_n()
Examples
combine_dimensions(mcmcr_example$alpha)
Combine MCMC samples of two objects
Description
Combines samples of two MCMC objects (with the same parameters, chains and iterations) using a function.
Usage
combine_samples(x, x2, fun = mean, ...)
Arguments
x |
An MCMC object. |
x2 |
a second MCMC object. |
fun |
The function to use to combine the samples. The function must return a scalar. |
... |
Unused. |
Value
The combined samples as an MCMC object with the same parameters, chains and iterations as the original objects.
See Also
Other combine:
combine_dimensions()
,
combine_samples_n()
Examples
combine_samples(mcmcr_example, mcmcr_example, fun = sum)
Combine MCMC samples of multiple objects
Description
Combines samples of multiple MCMC objects (with the same parameters, chains and iterations) using a function.
Usage
combine_samples_n(x, ..., fun = mean)
Arguments
x |
An MCMC object (or a list of mcmc objects). |
... |
Additional MCMC objects. |
fun |
A function. |
See Also
Other combine:
combine_dimensions()
,
combine_samples()
Examples
combine_samples_n(mcmcr_example, mcmcr_example, mcmcr_example, fun = sum)
Converged
Description
Tests whether an object has converged.
Usage
## Default S3 method:
converged(
x,
rhat = 1.1,
esr = 0.33,
by = "all",
as_df = FALSE,
na_rm = FALSE,
...
)
Arguments
x |
An object. |
rhat |
The maximum rhat value. |
esr |
The minimum effective sampling rate. |
by |
A string indicating whether to determine by "term", "parameter" or "all". |
as_df |
A flag indicating whether to return the results as a data frame versus a named list. |
na_rm |
A flag specifying whether to ignore missing values. |
... |
Other arguments passed to methods. |
Value
A logical scalar indicating whether the object has converged.
See Also
Other convergence:
converged_pars()
,
converged_terms()
,
esr()
,
esr_pars()
,
esr_terms()
,
rhat()
,
rhat_pars()
,
rhat_terms()
Examples
converged(mcmcr_example)
Converged
Description
Tests whether an object has converged.
Usage
## S3 method for class 'mcmcrs'
converged(
x,
rhat = 1.1,
esr = 0.33,
by = "all",
as_df = FALSE,
bound = FALSE,
na_rm = FALSE,
...
)
Arguments
x |
An object. |
rhat |
The maximum rhat value. |
esr |
The minimum effective sampling rate. |
by |
A string indicating whether to determine by "term", "parameter" or "all". |
as_df |
A flag indicating whether to return the results as a data frame versus a named list. |
bound |
flag specifying whether to bind mcmcrs objects by their chains before calculating rhat. |
na_rm |
A flag specifying whether to ignore missing values. |
... |
Other arguments passed to methods. |
Value
A logical scalar indicating whether the object has converged.
See Also
Other convergence:
converged_pars()
,
converged_terms()
,
esr()
,
esr_pars()
,
esr_terms()
,
rhat()
,
rhat_pars()
,
rhat_terms()
Examples
converged(mcmcrs(mcmcr_example, mcmcr_example))
converged(mcmcrs(mcmcr_example, mcmcr_example), bound = TRUE)
Effective Sampling Rate
Description
Calculates the effective sampling rate (esr
).
Usage
## S3 method for class 'mcarray'
esr(x, by = "all", as_df = FALSE, na_rm = FALSE, ...)
Arguments
x |
An object. |
by |
A string indicating whether to determine by "term", "parameter" or "all". |
as_df |
A flag indicating whether to return the results as a data frame versus a named list. |
na_rm |
A flag specifying whether to ignore missing values. |
... |
Other arguments passed to methods. |
Details
By default
\frac{1}{1 + 2 \sum_{k = 1}^\infty\rho_k(\theta)}
from Brooks et al. (2011) where the infinite sum is truncated at
lag k
when \rho_{k+1}(\theta) < 0
.
Value
A number between 0 and 1 indicating the esr value.
References
Brooks, S., Gelman, A., Jones, G.L., and Meng, X.-L. (Editors). 2011. Handbook for Markov Chain Monte Carlo. Taylor & Francis, Boca Raton.
See Also
Other convergence:
converged()
,
converged_pars()
,
converged_terms()
,
esr_pars()
,
esr_terms()
,
rhat()
,
rhat_pars()
,
rhat_terms()
Effective Sampling Rate
Description
Calculates the effective sampling rate (esr
).
Usage
## S3 method for class 'mcmc'
esr(x, by = "all", as_df = FALSE, na_rm = FALSE, ...)
Arguments
x |
An object. |
by |
A string indicating whether to determine by "term", "parameter" or "all". |
as_df |
A flag indicating whether to return the results as a data frame versus a named list. |
na_rm |
A flag specifying whether to ignore missing values. |
... |
Other arguments passed to methods. |
Details
By default
\frac{1}{1 + 2 \sum_{k = 1}^\infty\rho_k(\theta)}
from Brooks et al. (2011) where the infinite sum is truncated at
lag k
when \rho_{k+1}(\theta) < 0
.
Value
A number between 0 and 1 indicating the esr value.
References
Brooks, S., Gelman, A., Jones, G.L., and Meng, X.-L. (Editors). 2011. Handbook for Markov Chain Monte Carlo. Taylor & Francis, Boca Raton.
See Also
Other convergence:
converged()
,
converged_pars()
,
converged_terms()
,
esr_pars()
,
esr_terms()
,
rhat()
,
rhat_pars()
,
rhat_terms()
Effective Sampling Rate
Description
Calculates the effective sampling rate (esr
).
Usage
## S3 method for class 'mcmc.list'
esr(x, by = "all", as_df = FALSE, na_rm = FALSE, ...)
Arguments
x |
An object. |
by |
A string indicating whether to determine by "term", "parameter" or "all". |
as_df |
A flag indicating whether to return the results as a data frame versus a named list. |
na_rm |
A flag specifying whether to ignore missing values. |
... |
Other arguments passed to methods. |
Details
By default
\frac{1}{1 + 2 \sum_{k = 1}^\infty\rho_k(\theta)}
from Brooks et al. (2011) where the infinite sum is truncated at
lag k
when \rho_{k+1}(\theta) < 0
.
Value
A number between 0 and 1 indicating the esr value.
References
Brooks, S., Gelman, A., Jones, G.L., and Meng, X.-L. (Editors). 2011. Handbook for Markov Chain Monte Carlo. Taylor & Francis, Boca Raton.
See Also
Other convergence:
converged()
,
converged_pars()
,
converged_terms()
,
esr_pars()
,
esr_terms()
,
rhat()
,
rhat_pars()
,
rhat_terms()
Effective Sampling Rate
Description
Calculates the effective sampling rate (esr
).
Usage
## S3 method for class 'mcmcarray'
esr(x, by = "all", as_df = FALSE, na_rm = FALSE, ...)
Arguments
x |
An object. |
by |
A string indicating whether to determine by "term", "parameter" or "all". |
as_df |
A flag indicating whether to return the results as a data frame versus a named list. |
na_rm |
A flag specifying whether to ignore missing values. |
... |
Other arguments passed to methods. |
Details
By default
\frac{1}{1 + 2 \sum_{k = 1}^\infty\rho_k(\theta)}
from Brooks et al. (2011) where the infinite sum is truncated at
lag k
when \rho_{k+1}(\theta) < 0
.
Value
A number between 0 and 1 indicating the esr value.
References
Brooks, S., Gelman, A., Jones, G.L., and Meng, X.-L. (Editors). 2011. Handbook for Markov Chain Monte Carlo. Taylor & Francis, Boca Raton.
See Also
Other convergence:
converged()
,
converged_pars()
,
converged_terms()
,
esr_pars()
,
esr_terms()
,
rhat()
,
rhat_pars()
,
rhat_terms()
Effective Sampling Rate
Description
Calculates the effective sampling rate (esr
).
Usage
## S3 method for class 'mcmcr'
esr(x, by = "all", as_df = FALSE, na_rm = FALSE, ...)
Arguments
x |
An object. |
by |
A string indicating whether to determine by "term", "parameter" or "all". |
as_df |
A flag indicating whether to return the results as a data frame versus a named list. |
na_rm |
A flag specifying whether to ignore missing values. |
... |
Other arguments passed to methods. |
Details
By default
\frac{1}{1 + 2 \sum_{k = 1}^\infty\rho_k(\theta)}
from Brooks et al. (2011) where the infinite sum is truncated at
lag k
when \rho_{k+1}(\theta) < 0
.
Value
A number between 0 and 1 indicating the esr value.
References
Brooks, S., Gelman, A., Jones, G.L., and Meng, X.-L. (Editors). 2011. Handbook for Markov Chain Monte Carlo. Taylor & Francis, Boca Raton.
See Also
Other convergence:
converged()
,
converged_pars()
,
converged_terms()
,
esr_pars()
,
esr_terms()
,
rhat()
,
rhat_pars()
,
rhat_terms()
Examples
esr(mcmcr_example)
Effective Sampling Rate
Description
Calculates the effective sampling rate (esr
).
Usage
## S3 method for class 'mcmcrs'
esr(x, by = "all", as_df = FALSE, na_rm = FALSE, ...)
Arguments
x |
An object. |
by |
A string indicating whether to determine by "term", "parameter" or "all". |
as_df |
A flag indicating whether to return the results as a data frame versus a named list. |
na_rm |
A flag specifying whether to ignore missing values. |
... |
Other arguments passed to methods. |
Details
By default
\frac{1}{1 + 2 \sum_{k = 1}^\infty\rho_k(\theta)}
from Brooks et al. (2011) where the infinite sum is truncated at
lag k
when \rho_{k+1}(\theta) < 0
.
Value
A number between 0 and 1 indicating the esr value.
References
Brooks, S., Gelman, A., Jones, G.L., and Meng, X.-L. (Editors). 2011. Handbook for Markov Chain Monte Carlo. Taylor & Francis, Boca Raton.
See Also
Other convergence:
converged()
,
converged_pars()
,
converged_terms()
,
esr_pars()
,
esr_terms()
,
rhat()
,
rhat_pars()
,
rhat_terms()
Examples
esr(mcmcrs(mcmcr_example, mcmcr_example))
P-Value effective sample size
Description
Calculates the effective sample size based on esr()
.
Usage
ess(x, by = "all", as_df = FALSE)
Arguments
x |
An MCMC object. |
by |
A string indicating whether to determine by "term", "parameter" or "all". |
as_df |
A flag indicating whether to return the results as a data frame versus a named list. |
See Also
Examples
ess(mcmcr_example)
Estimates
Description
Calculates the estimates for an MCMC object.
Usage
## S3 method for class 'mcarray'
estimates(x, fun = median, as_df = FALSE, ...)
Arguments
x |
An object. |
fun |
A function that given a numeric vector returns a numeric scalar. |
as_df |
A flag indicating whether to return the results as a data frame versus a named list. |
... |
Optional arguments to fun. |
Value
A named list or data frame.
See Also
Other MCMC manipulations:
bind_chains()
,
bind_iterations()
,
collapse_chains()
,
split_chains()
Estimates
Description
Calculates the estimates for an MCMC object.
Usage
## S3 method for class 'mcmc'
estimates(x, fun = median, as_df = FALSE, ...)
Arguments
x |
An object. |
fun |
A function that given a numeric vector returns a numeric scalar. |
as_df |
A flag indicating whether to return the results as a data frame versus a named list. |
... |
Optional arguments to fun. |
Value
A named list or data frame.
See Also
Other MCMC manipulations:
bind_chains()
,
bind_iterations()
,
collapse_chains()
,
split_chains()
Estimates
Description
Calculates the estimates for an MCMC object.
Usage
## S3 method for class 'mcmc.list'
estimates(x, fun = median, as_df = FALSE, ...)
Arguments
x |
An object. |
fun |
A function that given a numeric vector returns a numeric scalar. |
as_df |
A flag indicating whether to return the results as a data frame versus a named list. |
... |
Optional arguments to fun. |
Value
A named list or data frame.
See Also
Other MCMC manipulations:
bind_chains()
,
bind_iterations()
,
collapse_chains()
,
split_chains()
Estimates
Description
Calculates the estimates for an MCMC object.
Usage
## S3 method for class 'mcmcarray'
estimates(x, fun = median, as_df = FALSE, ...)
Arguments
x |
An object. |
fun |
A function that given a numeric vector returns a numeric scalar. |
as_df |
A flag indicating whether to return the results as a data frame versus a named list. |
... |
Optional arguments to fun. |
Value
A named list or data frame.
See Also
Other MCMC manipulations:
bind_chains()
,
bind_iterations()
,
collapse_chains()
,
split_chains()
Estimates
Description
Calculates the estimates for an MCMC object.
Usage
## S3 method for class 'mcmcr'
estimates(x, fun = median, as_df = FALSE, ...)
Arguments
x |
An object. |
fun |
A function that given a numeric vector returns a numeric scalar. |
as_df |
A flag indicating whether to return the results as a data frame versus a named list. |
... |
Optional arguments to fun. |
Value
A named list or data frame.
See Also
Other MCMC manipulations:
bind_chains()
,
bind_iterations()
,
collapse_chains()
,
split_chains()
Examples
estimates(mcmcr_example)
Fill All Values
Description
Fills all of an object's (missing and non-missing) values while preserving the object's dimensionality and class.
Usage
## S3 method for class 'mcarray'
fill_all(x, value = 0, nas = TRUE, ...)
Arguments
x |
An object. |
value |
A scalar of the value to replace values with. |
nas |
A flag specifying whether to also fill missing values. |
... |
Other arguments passed to methods. |
Details
It should only be defined for objects with values of consistent class ie not standard data.frames.
Value
The modified object.
Methods (by class)
-
fill_all(logical)
: Fill All for logical Objects -
fill_all(integer)
: Fill All for integer Objects -
fill_all(numeric)
: Fill All for numeric Objects -
fill_all(character)
: Fill All for character Objects
See Also
Other fill:
fill_na()
Examples
# logical
fill_all(c(TRUE, NA, FALSE))
fill_all(c(TRUE, NA, FALSE, nas = FALSE))
fill_all(c(TRUE, NA, FALSE, value = NA))
# integer
fill_all(matrix(1:4, nrow = 2), value = -1)
# numeric
fill_all(c(1, 4, NA), value = TRUE)
fill_all(c(1, 4, NA), value = TRUE, nas = FALSE)
# character
fill_all(c("some", "words"), value = TRUE)
Fill All Values
Description
Fills all of an object's (missing and non-missing) values while preserving the object's dimensionality and class.
Usage
## S3 method for class 'mcmcarray'
fill_all(x, value = 0, nas = TRUE, ...)
Arguments
x |
An object. |
value |
A scalar of the value to replace values with. |
nas |
A flag specifying whether to also fill missing values. |
... |
Other arguments passed to methods. |
Details
It should only be defined for objects with values of consistent class ie not standard data.frames.
Value
The modified object.
Methods (by class)
-
fill_all(logical)
: Fill All for logical Objects -
fill_all(integer)
: Fill All for integer Objects -
fill_all(numeric)
: Fill All for numeric Objects -
fill_all(character)
: Fill All for character Objects
See Also
Other fill:
fill_na()
Examples
# logical
fill_all(c(TRUE, NA, FALSE))
fill_all(c(TRUE, NA, FALSE, nas = FALSE))
fill_all(c(TRUE, NA, FALSE, value = NA))
# integer
fill_all(matrix(1:4, nrow = 2), value = -1)
# numeric
fill_all(c(1, 4, NA), value = TRUE)
fill_all(c(1, 4, NA), value = TRUE, nas = FALSE)
# character
fill_all(c("some", "words"), value = TRUE)
Fill All Values
Description
Fills all of an object's (missing and non-missing) values while preserving the object's dimensionality and class.
Usage
## S3 method for class 'mcmcr'
fill_all(x, value = 0, nas = TRUE, ...)
Arguments
x |
An object. |
value |
A scalar of the value to replace values with. |
nas |
A flag specifying whether to also fill missing values. |
... |
Other arguments passed to methods. |
Details
It should only be defined for objects with values of consistent class ie not standard data.frames.
Value
The modified object.
Methods (by class)
-
fill_all(logical)
: Fill All for logical Objects -
fill_all(integer)
: Fill All for integer Objects -
fill_all(numeric)
: Fill All for numeric Objects -
fill_all(character)
: Fill All for character Objects
See Also
Other fill:
fill_na()
Examples
# logical
fill_all(c(TRUE, NA, FALSE))
fill_all(c(TRUE, NA, FALSE, nas = FALSE))
fill_all(c(TRUE, NA, FALSE, value = NA))
# integer
fill_all(matrix(1:4, nrow = 2), value = -1)
# numeric
fill_all(c(1, 4, NA), value = TRUE)
fill_all(c(1, 4, NA), value = TRUE, nas = FALSE)
# character
fill_all(c("some", "words"), value = TRUE)
Fill Missing Values
Description
Fills all of an object's missing values while preserving the object's dimensionality and class.
Usage
## S3 method for class 'mcarray'
fill_na(x, value = 0, ...)
Arguments
x |
An object. |
value |
A scalar of the value to replace values with. |
... |
Other arguments passed to methods. |
Details
It should only be defined for objects with values of consistent class ie not standard data.frames.
Value
The modified object.
Methods (by class)
-
fill_na(logical)
: Fill Missing Values for logical Objects -
fill_na(integer)
: Fill Missing Values for integer Objects -
fill_na(numeric)
: Fill Missing Values for numeric Objects -
fill_na(character)
: Fill Missing Values for character Objects
See Also
Other fill:
fill_all()
Examples
# logical
fill_na(c(TRUE, NA))
# integer
fill_na(c(1L, NA), 0)
# numeric
fill_na(c(1, NA), Inf)
# character
fill_na(c("text", NA))
fill_na(matrix(c("text", NA)), value = Inf)
Fill Missing Values
Description
Fills all of an object's missing values while preserving the object's dimensionality and class.
Usage
## S3 method for class 'mcmcarray'
fill_na(x, value = 0, ...)
Arguments
x |
An object. |
value |
A scalar of the value to replace values with. |
... |
Other arguments passed to methods. |
Details
It should only be defined for objects with values of consistent class ie not standard data.frames.
Value
The modified object.
Methods (by class)
-
fill_na(logical)
: Fill Missing Values for logical Objects -
fill_na(integer)
: Fill Missing Values for integer Objects -
fill_na(numeric)
: Fill Missing Values for numeric Objects -
fill_na(character)
: Fill Missing Values for character Objects
See Also
Other fill:
fill_all()
Examples
# logical
fill_na(c(TRUE, NA))
# integer
fill_na(c(1L, NA), 0)
# numeric
fill_na(c(1, NA), Inf)
# character
fill_na(c("text", NA))
fill_na(matrix(c("text", NA)), value = Inf)
Fill Missing Values
Description
Fills all of an object's missing values while preserving the object's dimensionality and class.
Usage
## S3 method for class 'mcmcr'
fill_na(x, value = 0, ...)
Arguments
x |
An object. |
value |
A scalar of the value to replace values with. |
... |
Other arguments passed to methods. |
Details
It should only be defined for objects with values of consistent class ie not standard data.frames.
Value
The modified object.
Methods (by class)
-
fill_na(logical)
: Fill Missing Values for logical Objects -
fill_na(integer)
: Fill Missing Values for integer Objects -
fill_na(numeric)
: Fill Missing Values for numeric Objects -
fill_na(character)
: Fill Missing Values for character Objects
See Also
Other fill:
fill_all()
Examples
# logical
fill_na(c(TRUE, NA))
# integer
fill_na(c(1L, NA), 0)
# numeric
fill_na(c(1, NA), Inf)
# character
fill_na(c("text", NA))
fill_na(matrix(c("text", NA)), value = Inf)
Is mcarray object
Description
Tests whether an object is an mcarray.
Usage
is.mcarray(x)
Arguments
x |
The object to test. |
Value
A flag indicating whether the test was positive.
See Also
Other is:
is.mcmcarray()
,
is.mcmcr()
,
is.mcmcrs()
Examples
is.mcarray(mcmcr_example)
Is mcmcarray object
Description
Tests whether an object is an mcmcarray-object()
.
Usage
is.mcmcarray(x)
Arguments
x |
The object to test. |
Value
A flag indicating whether the test was positive.
See Also
Other is:
is.mcarray()
,
is.mcmcr()
,
is.mcmcrs()
Examples
is.mcmcarray(mcmcr_example$beta)
Is mcmcr object
Description
Tests whether an object is an mcmcr-object()
.
Usage
is.mcmcr(x)
Arguments
x |
The object to test. |
Value
A flag indicating whether the test was positive.
See Also
Other is:
is.mcarray()
,
is.mcmcarray()
,
is.mcmcrs()
Examples
is.mcmcr(mcmcr_example)
Is mcmcrs object
Description
Tests whether an object is an mcmcrs-object()
.
Usage
is.mcmcrs(x)
Arguments
x |
The object to test. |
Value
A flag indicating whether the test was positive.
See Also
Other is:
is.mcarray()
,
is.mcmcarray()
,
is.mcmcr()
Examples
is.mcmcrs(mcmcrs(mcmcr_example))
MCMC object transposition
Description
Transpose an MCMC object by permuting its parameter dimensions.
Usage
mcmc_aperm(x, perm, ...)
Arguments
x |
The MCMC object to transpose. Missing parameter dimensions are added on the end. If perm = NULL (the default) the parameter dimensions are reversed. |
perm |
A integer vector of the new order for the parameter dimensions. |
... |
Unused. |
Value
The modified MCMC object
See Also
Other manipulate:
mcmc_map()
MCMC map
Description
Adjust the sample values of an MCMC object using a function.
Usage
mcmc_map(.x, .f, .by = 1:npdims(.x), ...)
Arguments
.x |
An MCMC object |
.f |
The function to use |
.by |
A positive integer vector of the dimensions to apply the function over. |
... |
Additional arguments passed to .f. |
Value
The updated MCMC object.
See Also
Other manipulate:
mcmc_aperm()
Examples
mcmc_map(mcmcr_example$beta, exp)
mcmcarray
Description
An mcmcarray
object is an an array where the
first dimension is the chains, the second dimension is the iterations
and the subsequent dimensions represent the dimensionality of the parameter.
The name mcmcarray
reflects the fact that the MCMC dimensions,
ie the chains and iterations, precede the parameter dimensions.
See Also
Other objects:
mcmcr-object
,
mcmcrs-object
Examples
mcmcr_example$beta
mcmcr
Description
An mcmcr
object stores multiple uniquely named mcmcarray-object()
objects with the same number of chains and iterations.
Details
mcmcr
objects allow a set of dimensionality preserving parameters
to be manipulated and queried as a whole.
See Also
Other objects:
mcmcarray-object
,
mcmcrs-object
Examples
mcmcr_example
An example mcmcr object
Description
An example mcmcr-object()
derived from coda::line()
.
Usage
mcmcr_example
Format
An object of class mcmcr
of length 3.
Examples
mcmcr_example
Create mcmcrs
Description
Creates an mcmcrs-object()
from multiple link{mcmcr-object}
s.
Usage
mcmcrs(...)
Arguments
... |
Objects of class mcmcr. |
Value
An object of class mcmcrs
See Also
Other coerce:
as.mcarray()
,
as.mcmcarray()
,
as.mcmcr()
Examples
mcmcrs(mcmcr_example, mcmcr_example)
mcmcrs
Description
An mcmcrs
object stores multiple mcmcr-object()
s
with the same parameters and the same number of chains and iterations.
Details
mcmcrs
objects allow the results of multiple analyses
using the same model to be manipulated and queried as a whole.
See Also
Other objects:
mcmcarray-object
,
mcmcr-object
Examples
mcmcrs(mcmcr_example, mcmcr_example)
Number of Chains
Description
Gets the number of chains of an MCMC object.
Usage
## S3 method for class 'matrix'
nchains(x, ...)
Arguments
x |
An object. |
... |
Other arguments passed to methods. |
Value
An integer scalar of the number of chains.
See Also
Other MCMC dimensions:
niters()
,
npars()
,
nsams()
,
nsims()
,
nterms()
Number of Chains
Description
Gets the number of chains of an MCMC object.
Usage
## S3 method for class 'mcarray'
nchains(x, ...)
Arguments
x |
An object. |
... |
Other arguments passed to methods. |
Value
An integer scalar of the number of chains.
See Also
Other MCMC dimensions:
niters()
,
npars()
,
nsams()
,
nsims()
,
nterms()
Number of Chains
Description
Gets the number of chains of an MCMC object.
Usage
## S3 method for class 'mcmcarray'
nchains(x, ...)
Arguments
x |
An object. |
... |
Other arguments passed to methods. |
Value
An integer scalar of the number of chains.
See Also
Other MCMC dimensions:
niters()
,
npars()
,
nsams()
,
nsims()
,
nterms()
Number of Chains
Description
Gets the number of chains of an MCMC object.
Usage
## S3 method for class 'mcmcr'
nchains(x, ...)
Arguments
x |
An object. |
... |
Other arguments passed to methods. |
Value
An integer scalar of the number of chains.
See Also
Other MCMC dimensions:
niters()
,
npars()
,
nsams()
,
nsims()
,
nterms()
Number of Chains
Description
Gets the number of chains of an MCMC object.
Usage
## S3 method for class 'mcmcrs'
nchains(x, ...)
Arguments
x |
An object. |
... |
Other arguments passed to methods. |
Value
An integer scalar of the number of chains.
See Also
Other MCMC dimensions:
niters()
,
npars()
,
nsams()
,
nsims()
,
nterms()
Number of Iterations
Description
Gets the number of iterations (in a chain) of an MCMC object.
Usage
## S3 method for class 'matrix'
niters(x, ...)
Arguments
x |
An object. |
... |
Other arguments passed to methods. |
Value
An integer scalar of the number of iterations.
See Also
Other MCMC dimensions:
nchains()
,
npars()
,
nsams()
,
nsims()
,
nterms()
Number of Iterations
Description
Gets the number of iterations (in a chain) of an MCMC object.
Usage
## S3 method for class 'mcarray'
niters(x, ...)
Arguments
x |
An object. |
... |
Other arguments passed to methods. |
Value
An integer scalar of the number of iterations.
See Also
Other MCMC dimensions:
nchains()
,
npars()
,
nsams()
,
nsims()
,
nterms()
Number of Iterations
Description
Gets the number of iterations (in a chain) of an MCMC object.
Usage
## S3 method for class 'mcmcarray'
niters(x, ...)
Arguments
x |
An object. |
... |
Other arguments passed to methods. |
Value
An integer scalar of the number of iterations.
See Also
Other MCMC dimensions:
nchains()
,
npars()
,
nsams()
,
nsims()
,
nterms()
Number of Iterations
Description
Gets the number of iterations (in a chain) of an MCMC object.
Usage
## S3 method for class 'mcmcr'
niters(x, ...)
Arguments
x |
An object. |
... |
Other arguments passed to methods. |
Value
An integer scalar of the number of iterations.
See Also
Other MCMC dimensions:
nchains()
,
npars()
,
nsams()
,
nsims()
,
nterms()
Number of Iterations
Description
Gets the number of iterations (in a chain) of an MCMC object.
Usage
## S3 method for class 'mcmcrs'
niters(x, ...)
Arguments
x |
An object. |
... |
Other arguments passed to methods. |
Value
An integer scalar of the number of iterations.
See Also
Other MCMC dimensions:
nchains()
,
npars()
,
nsams()
,
nsims()
,
nterms()
Number of Parameters
Description
Gets the number of parameters of an object.
The default methods returns the length of pars()
if none are
NA
, otherwise it returns NA
.
Usage
## S3 method for class 'mcarray'
npars(x, scalar = NULL, ...)
Arguments
x |
An object. |
scalar |
A logical scalar specifying whether to include all parameters (NULL), only scalars (TRUE) or all parameters except scalars (FALSE). |
... |
Other arguments passed to methods. |
Value
An integer scalar of the number of parameters.
See Also
Other MCMC dimensions:
nchains()
,
niters()
,
nsams()
,
nsims()
,
nterms()
Other parameters:
pars()
,
set_pars()
Number of Parameters
Description
Gets the number of parameters of an object.
The default methods returns the length of pars()
if none are
NA
, otherwise it returns NA
.
Usage
## S3 method for class 'mcmcarray'
npars(x, scalar = NULL, ...)
Arguments
x |
An object. |
scalar |
A logical scalar specifying whether to include all parameters (NULL), only scalars (TRUE) or all parameters except scalars (FALSE). |
... |
Other arguments passed to methods. |
Value
An integer scalar of the number of parameters.
See Also
Other MCMC dimensions:
nchains()
,
niters()
,
nsams()
,
nsims()
,
nterms()
Other parameters:
pars()
,
set_pars()
Number of Parameters
Description
Gets the number of parameters of an object.
The default methods returns the length of pars()
if none are
NA
, otherwise it returns NA
.
Usage
## S3 method for class 'mcmcr'
npars(x, scalar = NULL, ...)
Arguments
x |
An object. |
scalar |
A logical scalar specifying whether to include all parameters (NULL), only scalars (TRUE) or all parameters except scalars (FALSE). |
... |
Other arguments passed to methods. |
Value
An integer scalar of the number of parameters.
See Also
Other MCMC dimensions:
nchains()
,
niters()
,
nsams()
,
nsims()
,
nterms()
Other parameters:
pars()
,
set_pars()
Number of Parameter Dimensions
Description
Gets the number of the dimensions of each parameter of an object.
The default methods returns the length of each element of pdims()
as an integer vector.
Usage
## S3 method for class 'mcmcarray'
npdims(x, ...)
Arguments
x |
An object. |
... |
Other arguments passed to methods. |
Value
A named integer vector of the number of dimensions of each parameter.
See Also
Other dimensions:
dims()
,
ndims()
,
pdims()
Number of Parameter Dimensions
Description
Gets the number of the dimensions of each parameter of an object.
The default methods returns the length of each element of pdims()
as an integer vector.
Usage
## S3 method for class 'mcmcr'
npdims(x, ...)
Arguments
x |
An object. |
... |
Other arguments passed to methods. |
Value
A named integer vector of the number of dimensions of each parameter.
See Also
Other dimensions:
dims()
,
ndims()
,
pdims()
Number of Terms
Description
Gets the number of terms of an MCMC object.
Usage
## S3 method for class 'mcmcarray'
nterms(x, ...)
Arguments
x |
An object. |
... |
Other arguments passed to methods. |
Value
A integer scalar of the number of terms.
See Also
Other MCMC dimensions:
nchains()
,
niters()
,
npars()
,
nsams()
,
nsims()
Number of Terms
Description
Gets the number of terms of an MCMC object.
Usage
## S3 method for class 'mcmcr'
nterms(x, ...)
Arguments
x |
An object. |
... |
Other arguments passed to methods. |
Value
A integer scalar of the number of terms.
See Also
Other MCMC dimensions:
nchains()
,
niters()
,
npars()
,
nsams()
,
nsims()
Number of Terms
Description
Gets the number of terms of an MCMC object.
Usage
## S3 method for class 'mcmcrs'
nterms(x, ...)
Arguments
x |
An object. |
... |
Other arguments passed to methods. |
Value
A integer scalar of the number of terms.
See Also
Other MCMC dimensions:
nchains()
,
niters()
,
npars()
,
nsams()
,
nsims()
Parameter descriptions
Description
Parameter descriptions
Arguments
x |
An object. |
scalar |
A logical scalar specifying whether to include all parameters (NULL), only scalars (TRUE) or all parameters except scalars (FALSE). |
terms |
A logical scalar specifying whether to provide the parameters for each term. |
nas |
A flag specifying whether to also fill missing values. |
nthin |
A positive integer of the thinning rate. |
by |
A string indicating whether to determine by "term", "parameter" or "all". |
as_df |
A flag indicating whether to return the results as a data frame versus a named list. |
fun |
A function that given a numeric vector returns a numeric scalar. |
bound |
flag specifying whether to bind mcmcrs objects by their chains before calculating rhat. |
rhat |
The maximum rhat value. |
esr |
The minimum effective sampling rate. |
na_rm |
A flag specifying whether to ignore missing values. |
parameters |
A character vector (or NULL) of the parameters to subset by. |
iterations |
An integer vector (or NULL) of the iterations to subset by. |
... |
Unused. |
x2 |
a second MCMC object. |
x_name |
A string of the name of the object. |
error |
A flag indicating whether to throw an informative error or immediately generate an informative message if the check fails. |
sorted |
A flag specifying whether the parameters must be sorted. |
object |
The MCMC object to get the coefficients for |
conf_level |
A number specifying the confidence level. By default 0.95. |
estimate |
The function to use to calculate the estimate. |
simplify |
A flag specifying whether to return just the estimate, lower, upper and svalue. |
perm |
A integer vector of the new order for the parameter dimensions. |
pars |
A character vector (or NULL) of the pars to zero. |
name |
A string specifying the parameter name. |
Parameter Names
Description
Gets the parameter names.
Usage
## S3 method for class 'mcmcr'
pars(x, scalar = NULL, terms = FALSE, ...)
Arguments
x |
An object. |
scalar |
A logical scalar specifying whether to include all parameters (NULL), only scalars (TRUE) or all parameters except scalars (FALSE). |
terms |
A logical scalar specifying whether to provide the parameters for each term. |
... |
Other arguments passed to methods. |
Value
A character vector of the names of the parameters.
See Also
Other parameters:
npars()
,
set_pars()
Parameter Names
Description
Gets the parameter names.
Usage
## S3 method for class 'mcmcrs'
pars(x, scalar = NULL, terms = FALSE, ...)
Arguments
x |
An object. |
scalar |
A logical scalar specifying whether to include all parameters (NULL), only scalars (TRUE) or all parameters except scalars (FALSE). |
terms |
A logical scalar specifying whether to provide the parameters for each term. |
... |
Other arguments passed to methods. |
Value
A character vector of the names of the parameters.
See Also
Other parameters:
npars()
,
set_pars()
Parameter Dimensions
Description
Gets the dimensions of each parameter of an object.
Usage
## S3 method for class 'mcarray'
pdims(x, ...)
Arguments
x |
An object. |
... |
Other arguments passed to methods. |
Value
A named list of integer vectors of the dimensions of each parameter.
See Also
Other dimensions:
dims()
,
ndims()
,
npdims()
Parameter Dimensions
Description
Gets the dimensions of each parameter of an object.
Usage
## S3 method for class 'mcmcarray'
pdims(x, ...)
Arguments
x |
An object. |
... |
Other arguments passed to methods. |
Value
A named list of integer vectors of the dimensions of each parameter.
See Also
Other dimensions:
dims()
,
ndims()
,
npdims()
Parameter Dimensions
Description
Gets the dimensions of each parameter of an object.
Usage
## S3 method for class 'mcmcr'
pdims(x, ...)
Arguments
x |
An object. |
... |
Other arguments passed to methods. |
Value
A named list of integer vectors of the dimensions of each parameter.
See Also
Other dimensions:
dims()
,
ndims()
,
npdims()
Objects exported from other packages
Description
These objects are imported from other packages. Follow the links below to see their documentation.
- coda
- extras
- generics
- nlist
- stats
- term
- universals
bind_chains
,bind_iterations
,collapse_chains
,converged
,dims
,esr
,estimates
,nchains
,niters
,npars
,npdims
,nterms
,pars
,pars<-
,pdims
,rhat
,set_pars
,split_chains
R-hat
Description
Calculates an R-hat (potential scale reduction factor) value.
Usage
## S3 method for class 'mcarray'
rhat(x, by = "all", as_df = FALSE, na_rm = FALSE, ...)
Arguments
x |
An object. |
by |
A string indicating whether to determine by "term", "parameter" or "all". |
as_df |
A flag indicating whether to return the results as a data frame versus a named list. |
na_rm |
A flag specifying whether to ignore missing values. |
... |
Other arguments passed to methods. |
Details
By default the uncorrected, unfolded, univariate, split R-hat value.
Value
A number >= 1 indicating the rhat value.
References
Gelman, A., and Rubin, D.B. 1992. Inference from Iterative Simulation Using Multiple Sequences. Statistical Science 7(4): 457–472.
See Also
Other convergence:
converged()
,
converged_pars()
,
converged_terms()
,
esr()
,
esr_pars()
,
esr_terms()
,
rhat_pars()
,
rhat_terms()
R-hat
Description
Calculates an R-hat (potential scale reduction factor) value.
Usage
## S3 method for class 'mcmc'
rhat(x, by = "all", as_df = FALSE, na_rm = FALSE, ...)
Arguments
x |
An object. |
by |
A string indicating whether to determine by "term", "parameter" or "all". |
as_df |
A flag indicating whether to return the results as a data frame versus a named list. |
na_rm |
A flag specifying whether to ignore missing values. |
... |
Other arguments passed to methods. |
Details
By default the uncorrected, unfolded, univariate, split R-hat value.
Value
A number >= 1 indicating the rhat value.
References
Gelman, A., and Rubin, D.B. 1992. Inference from Iterative Simulation Using Multiple Sequences. Statistical Science 7(4): 457–472.
See Also
Other convergence:
converged()
,
converged_pars()
,
converged_terms()
,
esr()
,
esr_pars()
,
esr_terms()
,
rhat_pars()
,
rhat_terms()
R-hat
Description
Calculates an R-hat (potential scale reduction factor) value.
Usage
## S3 method for class 'mcmc.list'
rhat(x, by = "all", as_df = FALSE, na_rm = FALSE, ...)
Arguments
x |
An object. |
by |
A string indicating whether to determine by "term", "parameter" or "all". |
as_df |
A flag indicating whether to return the results as a data frame versus a named list. |
na_rm |
A flag specifying whether to ignore missing values. |
... |
Other arguments passed to methods. |
Details
By default the uncorrected, unfolded, univariate, split R-hat value.
Value
A number >= 1 indicating the rhat value.
References
Gelman, A., and Rubin, D.B. 1992. Inference from Iterative Simulation Using Multiple Sequences. Statistical Science 7(4): 457–472.
See Also
Other convergence:
converged()
,
converged_pars()
,
converged_terms()
,
esr()
,
esr_pars()
,
esr_terms()
,
rhat_pars()
,
rhat_terms()
R-hat
Description
Calculates an R-hat (potential scale reduction factor) value.
Usage
## S3 method for class 'mcmcarray'
rhat(x, by = "all", as_df = FALSE, na_rm = FALSE, ...)
Arguments
x |
An object. |
by |
A string indicating whether to determine by "term", "parameter" or "all". |
as_df |
A flag indicating whether to return the results as a data frame versus a named list. |
na_rm |
A flag specifying whether to ignore missing values. |
... |
Other arguments passed to methods. |
Details
By default the uncorrected, unfolded, univariate, split R-hat value.
Value
A number >= 1 indicating the rhat value.
References
Gelman, A., and Rubin, D.B. 1992. Inference from Iterative Simulation Using Multiple Sequences. Statistical Science 7(4): 457–472.
See Also
Other convergence:
converged()
,
converged_pars()
,
converged_terms()
,
esr()
,
esr_pars()
,
esr_terms()
,
rhat_pars()
,
rhat_terms()
R-hat
Description
Calculates an R-hat (potential scale reduction factor) value.
Usage
## S3 method for class 'mcmcr'
rhat(x, by = "all", as_df = FALSE, na_rm = FALSE, ...)
Arguments
x |
An object. |
by |
A string indicating whether to determine by "term", "parameter" or "all". |
as_df |
A flag indicating whether to return the results as a data frame versus a named list. |
na_rm |
A flag specifying whether to ignore missing values. |
... |
Other arguments passed to methods. |
Details
By default the uncorrected, unfolded, univariate, split R-hat value.
Value
A number >= 1 indicating the rhat value.
References
Gelman, A., and Rubin, D.B. 1992. Inference from Iterative Simulation Using Multiple Sequences. Statistical Science 7(4): 457–472.
See Also
Other convergence:
converged()
,
converged_pars()
,
converged_terms()
,
esr()
,
esr_pars()
,
esr_terms()
,
rhat_pars()
,
rhat_terms()
Examples
rhat(mcmcr_example)
rhat(mcmcr_example, by = "parameter")
rhat(mcmcr_example, by = "term")
rhat(mcmcr_example, by = "term", as_df = TRUE)
R-hat
Description
Calculates an R-hat (potential scale reduction factor) value.
Usage
## S3 method for class 'mcmcrs'
rhat(x, by = "all", as_df = FALSE, na_rm = FALSE, bound = FALSE, ...)
Arguments
x |
An object. |
by |
A string indicating whether to determine by "term", "parameter" or "all". |
as_df |
A flag indicating whether to return the results as a data frame versus a named list. |
na_rm |
A flag specifying whether to ignore missing values. |
bound |
flag specifying whether to bind mcmcrs objects by their chains before calculating rhat. |
... |
Other arguments passed to methods. |
Details
By default the uncorrected, unfolded, univariate, split R-hat value.
Value
A number >= 1 indicating the rhat value.
References
Gelman, A., and Rubin, D.B. 1992. Inference from Iterative Simulation Using Multiple Sequences. Statistical Science 7(4): 457–472.
See Also
Other convergence:
converged()
,
converged_pars()
,
converged_terms()
,
esr()
,
esr_pars()
,
esr_terms()
,
rhat_pars()
,
rhat_terms()
Examples
rhat(mcmcrs(mcmcr_example, mcmcr_example))
rhat(mcmcrs(mcmcr_example, mcmcr_example), bound = TRUE)
Set Parameters
Description
Sets an object's parameter names.
The assignment version pars<-()
forwards to set_pars()
.
Usage
## S3 method for class 'mcmcr'
set_pars(x, value, ...)
Arguments
x |
An object. |
value |
A character vector of the new parameter names. |
... |
Other arguments passed to methods. |
Details
value
must be a unique character vector of the same length as the
object's parameters.
Value
The modified object.
See Also
Other parameters:
npars()
,
pars()
Set Parameters
Description
Sets an object's parameter names.
The assignment version pars<-()
forwards to set_pars()
.
Usage
## S3 method for class 'mcmcrs'
set_pars(x, value, ...)
Arguments
x |
An object. |
value |
A character vector of the new parameter names. |
... |
Other arguments passed to methods. |
Details
value
must be a unique character vector of the same length as the
object's parameters.
Value
The modified object.
See Also
Other parameters:
npars()
,
pars()
Split Chains
Description
Splits each of an MCMC object's chains in half to double the number of chains and halve the number of iterations.
Usage
## S3 method for class 'mcmcarray'
split_chains(x, ...)
Arguments
x |
An object. |
... |
Other arguments passed to methods. |
Value
The modified object.
See Also
Other MCMC manipulations:
bind_chains()
,
bind_iterations()
,
collapse_chains()
,
estimates()
Split Chains
Description
Splits each of an MCMC object's chains in half to double the number of chains and halve the number of iterations.
Usage
## S3 method for class 'mcmcr'
split_chains(x, ...)
Arguments
x |
An object. |
... |
Other arguments passed to methods. |
Value
The modified object.
See Also
Other MCMC manipulations:
bind_chains()
,
bind_iterations()
,
collapse_chains()
,
estimates()
Subset an MCMC object
Description
Subsets an MCMC object by its chains, iterations and/or parameters.
Usage
## S3 method for class 'mcmcarray'
subset(x, chains = NULL, iters = NULL, iterations = NULL, ...)
## S3 method for class 'mcmcr'
subset(
x,
chains = NULL,
iters = NULL,
pars = NULL,
iterations = NULL,
parameters = NULL,
...
)
## S3 method for class 'mcmcrs'
subset(
x,
chains = NULL,
iters = NULL,
pars = NULL,
iterations = NULL,
parameters = NULL,
...
)
Arguments
x |
The MCMC object to subset |
chains |
An integer vector of chains. |
iters |
An integer vector of iterations. |
iterations |
An integer vector (or NULL) of the iterations to subset by. |
... |
Unused. |
pars |
A character vector of parameter names. |
parameters |
A character vector (or NULL) of the parameters to subset by. |
Methods (by class)
-
subset(mcmcarray)
: Subset an mcmcarray object -
subset(mcmcr)
: Subset an mcmcr object -
subset(mcmcrs)
: Subset an mcmcrs object
See Also
Examples
subset(mcmcr_example,
chains = 2L, iters = 1:100,
pars = c("beta", "alpha")
)
Validate MCMC objects
Description
Validates class and structure of MCMC objects.
Usage
vld_mcmcarray(x)
vld_mcmcr(x)
vld_mcmcrs(x)
Arguments
x |
The object to check. |
Details
To just validate class use chk::vld_s3_class()
.
Value
A flag indicating whether the object was validated.
Functions
-
vld_mcmcarray()
: Validatemcmcarray-object()
-
vld_mcmcr()
: Validatemcmcr-object()
-
vld_mcmcrs()
: Validatemcmcrs-object()
See Also
Examples
#' vld_mcmcarray
vld_mcmcarray(1)
# vld_mcmcr
vld_mcmcr(1)
vld_mcmcr(mcmcr::mcmcr_example)
# vld_mcmcrs
vld_mcmcrs(1)
Zero MCMC sample values
Description
Zeros an MCMC object's sample values.
Usage
zero(x, ...)
## S3 method for class 'mcarray'
zero(x, ...)
## S3 method for class 'mcmcarray'
zero(x, ...)
## S3 method for class 'mcmcr'
zero(x, pars = NULL, ...)
Arguments
x |
The MCMC object. |
... |
Unused. |
pars |
A character vector (or NULL) of the pars to zero. |
Details
It is used for removing the effect of a random effect where the expected value is 0.
Value
The MCMC
Methods (by class)
-
zero(mcarray)
: Zero an mcarray object -
zero(mcmcarray)
: Zero an mcmcarray object -
zero(mcmcr)
: Zero an mcmcr object
Examples
zero(mcmcr_example, pars = "beta")