Convert Frequency to Character

Description

This function converts a frequency to its string representation. The format is explained in the f.? functions.

Usage

## S3 method for class 'ldtf'
as.character(x, ...)

Arguments

Value

A string representation of the value of the frequency.

Convert a Variable to Character String

Description

Use this function to convert a variable to a compact form.

Usage

## S3 method for class 'ldtv'
as.character(x, ...)

Arguments

Details

The returned character will have just one line, with items separated by tab or semi-colon.

Value

A character that represents the variable.

Examples

# define the variable:
data <- c(1,2,3,2,3,4,5)
start_f <- f.monthly(2022,12)
fields <- list(c("key1","value1"), c("key2", "value2"))
v1 = variable(data,start_f, "V1", fields)

#string representation:
v1_str <- as.character(v1)

Convert Variable to Data Frame

Description

Use this function to convert a variable to a data frame. You can use the result for plotting.

Usage

## S3 method for class 'ldtv'
as.data.frame(x, ...)

Arguments

Value

A data frame in which row names are set from the frequency of the variable.

Examples

# Define the variable:
data <- c(1,2,3,2,3,4,5)
start_f <- f.monthly(2022,12)
fields <- list(c("key1","value1"), c("key2", "value2"))
v1 = variable(data,start_f,"V1", fields)

# convert it to data.frame
df1 <- as.data.frame(v1)

Convert Character String to Frequency

Description

Use this function to convert a character string back to a frequency. You need the class id information.

Usage

as.frequency(str, classId)

Arguments

Value

A frequency, which is an object of class 'ldtf'. See the f.? functions.

Coerce Variable to 'numeric'

Description

Coerce Variable to 'numeric'

Usage

## S3 method for class 'ldtv'
as.numeric(x, ...)

Arguments

Value

data in x.

Bind Variables and Create a Data.frame

Description

Use this function to bind variables with the same class of frequency together.

Usage

bind.variables(
  varList,
  interpolate = FALSE,
  adjustLeadLags = FALSE,
  numExo = 0,
  horizon = 0
)

Arguments

Value

A list with the following members:

Examples

v1 = variable(c(1,2,3,2,3,4,5),f.monthly(2022,12),"V1")
v2 = variable(c(10,20,30,20,30,40,50),f.monthly(2022,8),"V2")
L = bind.variables(list(v1,v2))

Convert Data to Year-Based Frequency

Description

Use this function to convert time-series data (currently implemented: daily) to time-series data with year-based frequency such as monthly, quarterly, yearly, etc.

Usage

convert.to.XxYear(variable, x, aggregateFun)

Arguments

Details

See the details section of the convert.to.daily function.

Value

A variable with year-based frequency.

Examples

startFreq <- f.daily(c(2023,1,1))
v <- variable(c(1:(365*2)), startFreq)
w <- convert.to.XxYear(v,12,function(x)mean(x))

Convert Data to Daily Frequency

Description

Use this function to convert a time-series data (currently implemented: Date-List, Daily-In-Week) to a time-series data with daily frequency.

Usage

convert.to.daily(variable, aggregateFun = NULL)

Arguments

Details

In some cases, conversion sorts the dates and fills any gaps between them with NA. However, in other cases, conversion requires aggregation. For example, when aggregating hourly data over a period of k hours to generate daily data, we expect k numbers in each interval. The aggregate function can be set to calculate the mean, variance, median, etc., or any function that takes the vector of k values and returns a number.

Value

A variable with daily frequency, with data sorted from the original variable and missing dates filled with NA.

Examples

startFreq <- f.list.date(c("20220904","20220901"), "20220901")
v <- variable(c(4,1), startFreq)
w <- convert.to.daily(v)

Convert Data to Multi-Day Frequency

Description

Use this function to convert a time-series data (currently implemented: daily) to a time-series data with multi-day frequency.

Usage

convert.to.multidaily(variable, k, aggregateFun, fromEnd = TRUE)

Arguments

Details

See the details section of the convert.to.daily function.

Value

A variable with multi-day frequency.

Examples

startFreq <- f.daily(c(2022, 9, 1))
v <- variable(c(1,2,3,4,5,6,7,8), startFreq)
w <- convert.to.multidaily(v, 3, function(x)mean(x, na.rm=TRUE))

Convert Data to Weekly Frequency

Description

Use this function to convert time-series data (currently implemented: daily) to time-series data with weekly frequency.

Usage

convert.to.weekly(variable, weekStart, aggregateFun)

Arguments

Details

See the details section of the convert.to.daily function.

Value

A variable with weekly frequency.

Examples

startFreq <- f.daily(c(2022, 9, 1))
v <- variable(c(1,2,3,4,5,6,7,8), startFreq)
w <- convert.to.weekly(v, "mon", function(x)mean(x, na.rm=TRUE))

Create a Cross-Section Frequency

Description

This frequency is typically used for indexed data. It is represented by an integer that indicates the position of the observation.

Usage

f.cross.section(position)

Arguments

Details

In order to use the as.frequency function for this type of frequency, you need the following information:

• Character Format "#" (the number is the position)

• Class Id "cs"

Value

An object of class ldtf which is also a list with the following members:

Examples

cs0 <- f.cross.section(10) # this initializes a cross-section frequency

cs0_value_str <-  as.character(cs0) # this will be '10'.
cs0_class_str <- get.class.id(cs0) # this will be 'cs'.

cs_new <- as.frequency("20", "cs")
#      this is a cross-section frequency. It points to position 20.

Create a Daily Frequency

Description

Use this function to create a frequency for time-series data that occurs daily.

Usage

f.daily(date)

Arguments

Details

To use the as.frequency function for this type of frequency, you need the following information:

• Character Format "YYYYMMDD" (similar to Weekly)

• Class Id "d"

Value

An object of class ldtf, which is also a list with the following members:

Examples

d0 <- f.daily(c(2023, 1, 2)) # This is 2/1/2023. Next observation belongs to 3/1/2023.

d0_value_str <-  as.character(d0) # this will be '20230102'.
d0_class_str <- get.class.id(d0) # this will be 'd'.

d_new <- as.frequency("20230109", "d") # This is 9/1/2023.

# Don't use invalid or unsupported dates:

# d_invalid <- try(as.frequency("1399109", "d")) # this is a too old date and unsupported
# d_invalid <- try(as.frequency("20230132", "d")) # invalid day in month
d_invalid <- try(as.frequency("20231331", "d")) # invalid month

Create a Daily-In-Week Frequency

Description

Use this function to create a frequency for time-series data that occurs daily within a subset of a week. The first day of the interval is used as the reference.

Usage

f.daily.in.week(date, weekStart = "mon", weekEnd = "fri", forward = TRUE)

Arguments

Details

In order to use the as.frequency function for this type of frequency, you need the following information:

• Character Format: The first day of the interval in "YYYYMMDD" format.

• Class Id: "i:...-..." (where the first '...' represents weekStart and the second '...' represents weekEnd; e.g., i:mon-fri means a week from Monday to Friday)

Value

An object of class ldtf. It is also a list with the following members:

Examples

dw0 <- f.daily.in.week(c(2023, 5, 16), "mon", "fri") # This is 16/5/2023.
dw0_value_str <-  as.character(dw0) # this will be '20230516'.
dw0_class_str <- get.class.id(dw0) # this will be 'i:mon-fri'.

# Let's use the same date with another week definition:
dw1 <- f.daily.in.week(c(2023, 5, 16), "wed", "sat")
#     This is NOT 16/5/2023. It is 17/5/2023.
#     Since it was outside the week, we moved it forward.
dw2 <- f.daily.in.week(c(2023, 5, 16), "wed", "sat", FALSE)
#     This is 13/5/2023. The original day was outside the
#     week, but we moved backward too the end of
#     the previous week (which is Saturday).

dw_new <- as.frequency("20230519", "i:sat-wed")
#     This is 20/1/2023 (by default, it moves forward).

# Don't use invalid or unsupported dates:

dw_invalid <- try(as.frequency("1399109", "d3")) # this is a too old date and unsupported
dw_invalid <- try(as.frequency("20230132", "d4")) # invalid day in month
dw_invalid <- try(as.frequency("20231331", "d5")) # invalid month

# don't use invalid week definitions:
dw_invalid <- try(f.daily.in.week(c(2023, 5, 16), "Wednesday", "sat"))

Create an 'Hourly' Frequency

Description

Use this function to create a frequency for time-series data that occurs hourly in a day or a subset of a week.

Usage

f.hourly(day, hour)

Arguments

Details

In order to use the as.frequency function for this type of frequency, you need the following information:

• Character Format: "YYYYMMDD:#" (where # represents the value of hour)

• Class Id: ho|... (where '...' represents the 'class id' of day)

Value

An object of class ldtf. It is also a list with the following members:

Examples

ho0 <- f.hourly(f.daily(c(2023,5,16)),4)

ho0_value_str <-  as.character(ho0) # this will be '20230516:4'.
ho0_class_str <- get.class.id(ho0)
#    this will be 'ho|d'. The second part (i.e., 'd')
#    shows that this frequency is defined in a 'Daily' frequency.

ho_new <- as.frequency("20231101:3", "ho|i:wed-sat")

# Don't make the following mistakes:

ho_invalid <- try(as.frequency("20231101:3", "ho|j:wed-sat"))
#  invalid format in day-based frequency
ho_invalid <- try(f.hourly(f.daily(c(2023,5,16)),25)) # invalid hour

Create a List-Date Frequency

Description

Use this frequency for data with date labels. It is generally a list of dates, but it can also be used to label observations outside this list.

Usage

f.list.date(items, value = NULL, reformat = TRUE)

Arguments

Details

In order to use the as.frequency function for this type of frequency, you need the following information:

• Character Format: "YYYYMMDD" (i.e., the item)

• Class Id: Ld or Ld:... (where '...' represents the semi-colon-separated items)

Value

An object of class ldtf. It is also a list with the following members:

Examples

Ld0 <- f.list.date(c("20231101","20220903","20200823","20230303"), "20200823")

Ld0_value_str <-  as.character(Ld0) # this will be '20200823'.
Ld0_class_str <- get.class.id(Ld0)
#      this will be 'Ld:20231101;20220903;20200823;20230303'.

Ld_new <- as.frequency("20231101", "Ld:20231101;20220903;20200823;20230303")
Ld_new0 <- as.frequency("20231101", "Ld")
#     compared to the previous one, its items will be empty

# Don't make the following mistakes:

Ld_invalid <- try(as.frequency("20231102", "Ld:20231101;20220903;20200823;20230303"))
  # 'E' is not a member of the list
Ld_invalid <- try(f.list.date(c("20231101","20220903","20200823","20230303"), "20231102"))

Create a List-String Frequency

Description

This frequency is typically used for labeled data. It is generally a list, but it can also be used to label observations outside this list.

Usage

f.list.string(items, value)

Arguments

Details

In order to use the as.frequency function for this type of frequency, you need the following information:

• Character Format: "..." (where '...' represents the value)

• Class Id: Ls or Ls:... (where '...' represents the semi-colon-separated items)

Value

An object of class ldtf, which is also a list with the following members:

Examples

L0 <- f.list.string(c("A","B","C","D"), "C")

L0_value_str <-  as.character(L0) # this will be 'C'.
L0_class_str <- get.class.id(L0) # this will be 'Ls:A;B;C;D'.

L_new <- as.frequency("A", "Ls:A;B;C;D")
L_new0 <- as.frequency("A", "Ls") # compared to the previous one, its items will be empty

# Don't make the following mistakes:

L_invalid <- try(as.frequency("E", "Ls:A;B;C;D")) # 'E' is not a member of the list
L_invalid <- try(f.list.string(c("A","B","C","D"), "E"))

Create a Minute-ly Frequency

Description

Use this function to create a frequency for time-series data that occurs every minute in a day or a subset of a week.

Usage

f.minutely(day, minute)

Arguments

Details

In order to use the as.frequency function for this type of frequency, you need the following information:

• Character Format: "YYYYMMDD:#" (where # represents the value of minute)

• Class Id: mi|... (where '...' represents the 'class id' of day)

Value

An object of class ldtf. It is also a list with the following members:

Examples

mi0 <- f.minutely(f.daily(c(2023,5,16)),1200)

mi0_value_str <-  as.character(mi0) # this will be '20230516:1200'.
mi0_class_str <- get.class.id(mi0)
#     this will be 'mi|d'. The second part (i.e., 'd')
#     shows that this frequency is defined in a 'Daily' frequency.

mi_new <- as.frequency("20231101:3", "mi|i:wed-sat")

# Don't make the following mistakes:

mi_invalid <- try(as.frequency("20231101:3", "mi|j:wed-sat"))
#   invalid format in day-based frequency
mi_invalid <- try(f.minutely(f.daily(c(2023,5,16)),2000)) # invalid minute

Create a Monthly Frequency

Description

Use this function to create a frequency for time-series data that occurs monthly.

Usage

f.monthly(year, month)

Arguments

Details

In order to use the as.frequency function for this type of frequency, you need the following information:

• Character Format "#m#" (first # is the year, second # is the month (1 to 12); e.g., 2010m8 or 2010m12. Note that 2000m0 or 2000m13 are invalid.

• Class Id "m"

Value

An object of class ldtf which is also a list with the following members:

Examples

m0 <- f.monthly(2020, 2)
#     this is a monthly frequency that refers to the second month of the year 2020.

m0_value_str <-  as.character(m0) # this will be '2020M2'.
m0_class_str <- get.class.id(m0) # this will be 'm'.

m_new <- as.frequency("2021m3", "m")
#     this is a monthly frequency that refers to the third month of the year 2021.

# Don't make the following mistakes:

m_invalid <- try(f.monthly(2020, 0))
m_invalid <- try(f.monthly(2020, 5))
m_invalid <- try(as.frequency("2021m0", "m"))
m_invalid <- try(as.frequency("2021m13", "m"))
m_invalid <- try(as.frequency("2021", "m"))

Create a Multi-Day Frequency

Description

Use this function to create a frequency for time-series data that occurs every k days. The first day of the interval is used as the reference.

Usage

f.multi.daily(date, k)

Arguments

Details

In order to use the as.frequency function for this type of frequency, you need the following information:

• Character Format: The first day of the interval in "YYYYMMDD" format.

• Class Id: "d#" (where # is the value of k; e.g., d3 means every 3 days)

Value

An object of class ldtf. It is also a list with the following members:

Examples

md0 <- f.multi.daily(c(2023, 1, 2), 4) # This is 2/1/2023. Next observation belongs to 6/1/2023.

md0_value_str <-  as.character(md0) # this will be '20230102'.
md0_class_str <- get.class.id(md0) # this will be 'd4'.

md_new <- as.frequency("20230109", "d") # This is 9/1/2023.

# Don't use invalid or unsupported dates:

md_invalid <- try(as.frequency("1399109", "d3")) # this is a too old date and unsupported
md_invalid <- try(as.frequency("20230132", "d4")) # invalid day in month
md_invalid <- try(as.frequency("20231331", "d5")) # invalid month

Create a Multi-Week Frequency

Description

Use this function to create a frequency for time-series data that occurs every 'k' weeks. The first day of the first week is used as the reference.

Usage

f.multi.weekly(date, k)

Arguments

Details

To use the as.frequency function for this type of frequency, you need the following information:

• Character Format The first day of the first week in "YYYYMMDD" format.

• Class Id "w#" (the number is the value of k; e.g., w3 means every 3 weeks)

Value

An object of class ldtf, which is also a list with the following members:

Examples

mw0 <- f.multi.weekly(c(2023, 1, 2), 3)
# This is 2/1/2023, which is Monday. The next observation belongs to 23/1/2023.

mw0_value_str <- as.character(mw0) # This will be '20230102'.
mw0_class_str <- get.class.id(mw0) # This will be 'w3'.

mw_new <- as.frequency("20230109", "w4") # This is 9/1/2023.

# Don't use invalid or unsupported dates:

mw_invalid <- try(as.frequency("1399109", "w4")) # this is a too old date and unsupported
mw_invalid <- try(as.frequency("20230132", "w5")) # invalid day in month
mw_invalid <- try(as.frequency("20231331", "w2")) # invalid month
mw_invalid <- try(as.frequency("20231012", "w0"))

Create a Multi-Year Frequency

Description

Use this function to create a frequency for time-series data that occurs every z years.

Usage

f.multi.yearly(year, z)

Arguments

Details

In order to use the as.frequency function for this type of frequency, you need the following information:

• Character Format "#" (the number is the year, which means the string representation is the first year of the interval)

• Class Id "z#" ('#' represents the value: z; e.g., z3 means every 3 years)

Value

An object of class ldtf which is also a list with the following members:

Examples

my0 <- f.multi.yearly(2020, 2)
#      this is a multi-year frequency that refers to the year 2020.
#      The next observation is expected in 2022 (not the next year).

my0_value_str <-  as.character(my0) # this will be '2020'.
my0_class_str <- get.class.id(my0) # this will be 'z2'.

my_new <- as.frequency("2020", "z3")
#      this is a multi-year frequency that refers to the year 2020.
#      However, the next observation is expected in 2023.

# Don't make the following mistakes:

my_invalid <- try(f.multi.yearly(2020, 0))
my_invalid <- try(f.multi.yearly(2020, -5))
my_invalid <- try(as.frequency("2021", "z"))

Create a Quarterly Frequency

Description

Use this function to create a frequency for time-series data that occurs quarterly.

Usage

f.quarterly(year, quarter)

Arguments

Details

In order to use the as.frequency function for this type of frequency, you need the following information:

• Character Format "#q#" (first '#' is the year, second '#' is the quarter; e.g., 2010q3 or 2010q4. Note that 2000q0 or 2000q5 are invalid.

• Class Id "q"

Value

An object of class ldtf which is also a list with the following members:

Examples

q0 <- f.quarterly(2020, 2)
#     this is a quarterly frequency that refers to the second quarter of the year 2021.

q0_value_str <-  as.character(q0) # this will be '2020Q2'.
q0_class_str <- get.class.id(q0) # this will be 'q'.

q_new <- as.frequency("2021q3", "q")
#      this is a quarterly frequency that refers to the third quarter of the year 2021.

# Don't make the following mistakes:

q_invalid <- try(f.quarterly(2020, 0))
q_invalid <- try(f.quarterly(2020, 5))
q_invalid <- try(as.frequency("2021q0", "q"))
q_invalid <- try(as.frequency("2021q5", "q"))
q_invalid <- try(as.frequency("2021", "q"))

Create a Second-ly Frequency

Description

Use this function to create a frequency for time-series data that occurs every second in a day or a subset of a week.

Usage

f.secondly(day, second)

Arguments

Details

In order to use the as.frequency function for this type of frequency, you need the following information:

• Character Format: "YYYYMMDD:#" (where # represents the value of second)

• Class Id: se|... (where '...' represents the 'class id' of day)

Value

An object of class ldtf. It is also a list with the following members:

Examples

se0 <- f.secondly(f.daily(c(2023,5,16)),40032)

se0_value_str <-  as.character(se0) # this will be '20230516:40032'.
se0_class_str <- get.class.id(se0)
#     this will be 'se|d'. The second part (i.e., 'd') shows
#     that this frequency is defined in a 'Daily' frequency.

se_new <- as.frequency("20231101:3", "se|i:wed-sat")

# Don't make the following mistakes:

mi_invalid <- try(as.frequency("20231101:3", "se|j:wed-sat"))
#  invalid format in day-based frequency
mi_invalid <- try(f.secondly(f.daily(c(2023,5,16)),100000)) # invalid second

Create a Weekly Frequency

Description

Use this function to create a frequency for time-series data that occurs weekly. The first day of the week is used as the reference.

Usage

f.weekly(date)

Arguments

Details

To use the as.frequency function for this type of frequency, you need the following information:

• Character Format The first day of the week in "YYYYMMDD" format.

• Class Id "w"

Value

An object of class ldtf, which is also a list with the following members:

Examples

w0 <- f.weekly(c(2023, 1, 2)) # This is 2/1/2023, which is Monday.
#    The next observation belongs to 9/1/2023.

w0_value_str <-  as.character(w0) # this will be '20230102'.
w0_class_str <- get.class.id(w0) # this will be 'w'.

w_new <- as.frequency("20230109", "w") # This is 9/1/2023.

# Don't use invalid or unsupported dates:

w_invalid <- try(as.frequency("1399109", "w")) # this is a too old date and unsupported
w_invalid <- try(as.frequency("20230132", "w")) # invalid day in month
w_invalid <- try(as.frequency("20231331", "w")) # invalid month

Create an X-Times-A-Day Frequency

Description

Use this function to create a frequency for time-series data that occurs x times in a day or a subset of a week.

Usage

f.x.times.a.day(day, x, position)

Arguments

Details

In order to use the as.frequency function for this type of frequency, you need the following information:

• Character Format: "#" (where '#' represents the value of position)

• Class Id: "da#|..." (where '#' represents the value of x and '...' represents the 'class id' of day)

Value

An object of class ldtf. It is also a list with the following members:

Examples

xd0 <- f.x.times.a.day(f.daily(c(2023,5,16)),13, 12)

xd0_value_str <-  as.character(xd0) # this will be '20230516:12'.
xd0_class_str <- get.class.id(xd0)
#      this will be 'da13|d'. The second part (i.e., 'd')
#      shows that this frequency is defined in a 'Daily' frequency.

xd_new <- as.frequency("20231101:3", "da3|i:wed-sat")

# Don't make the following mistakes:

xd_invalid <- try(as.frequency("20231101:3", "da|i:wed-sat"))
#  invalid format in day-based frequency
xd_invalid <- try(f.x.times.a.day(f.daily(c(2023,5,16)),4,0)) # invalid position

Create an X-Times-A-Year Frequency

Description

Use this function to create a frequency for time-series data that occurs x times every year.

Usage

f.x.times.a.year(year, x, position)

Arguments

Details

In order to use the as.frequency function for this type of frequency, you need the following information:

• Character Format "#:#" (first # is the year and the second # is the position; e.g., 2010:8/12 or 2010:10/10. Note that 2000:0/2 or 2000:13/12 are invalid.

• Class Id "y#" (the number is the value: x)

Value

An object of class ldtf which is also a list with the following members:

Examples

xty0 <- f.x.times.a.year(2020, 3, 1)
#      this frequency divides the year 2020 into 3 partitions
#      and refers to the first partition.

xty_value_str <-  as.character(xty0) # this will be '2020:1'.
xty_class_str <- get.class.id(xty0) # this will be 'y3'.

xty_new <- as.frequency("2021:24", "z24")
#     this frequency divides the year 2021 into 24 partitions
#     and refers to the last partition.

# Don't make the following mistakes:

xty_invalid <- try(f.x.times.a.year(2020, 3, 0))
xty_invalid <- try(f.x.times.a.year(2020, 24, 25))
xty_invalid <- try(as.frequency("2021:13", "y12"))
xty_invalid <- try(as.frequency("2021:0", "y1"))
xty_invalid <- try(as.frequency("2021", "y1"))

Create an X-Times-Z-Years Frequency

Description

Use this function to create a frequency for time-series data that occurs x times every z years.

Usage

f.x.times.z.years(year, x, z, position)

Arguments

Details

In order to use the as.frequency function for this type of frequency, you need the following information:

• Character Format "#:#" (Similar to X-Times-A-Year. Note that the string representation refers to the first year of the interval.)

• Class Id "x#z#" (first '#' is the value: x, second '#' is the value: z; e.g., x23z4 means 23 times every 4 years)

Value

An object of class ldtf, which is also a list with the following members:

Examples

xtzy0 <- f.x.times.z.years(2020, 3, 2, 3)
# This frequency divides the year 2020 into 3 partitions and
# refers to the last partition. The next observation
# belongs to 2022 (not the next year).

xtzy_value_str <- as.character(xtzy0) # This will be '2020:3'.
xtzy_class_str <- get.class.id(xtzy0) # This will be 'x3z2'.

xtzy_new <- as.frequency("2021:3", "x3z4")
# This frequency divides the year 2021 into 3 partitions
# and refers to the last partition. The next observation occurs after 4 years.

# Don't make the following mistakes:

xtzy_invalid <- try(f.x.times.z.years(2020, 3, 5, 0))
xtzy_invalid <- try(f.x.times.z.years(2020, 3, 0, 1))
xtzy_invalid <- try(as.frequency("2021:25", "x24y2"))

Create an Annual Frequency

Description

Use this function to create a frequency for time-series data that occurs annually.

Usage

f.yearly(year)

Arguments

Details

In order to use the as.frequency function for this type of frequency, you need the following information:

• Character Format "#" (the number is the year)

• Class Id "y"

Value

An object of class ldtf which is also a list with the following members:

Examples

y0 <- f.yearly(2020) # this initializes a 'yearly' frequency

y0_value_str <-  as.character(y0) # this will be '2020'.
y0_class_str <- get.class.id(y0) # this will be 'y'.

y_new <- as.frequency("2021", "y") # this is a yearly frequency. It points to year 2021.

Get the Class Id of a Frequency

Description

Use this function to get the 'id' of a frequency class.

Usage

get.class.id(frequency)

Arguments

Details

You need this 'id' to convert the character back to the object. Some frequencies have a constant class id, such as 'm' for 'monthly' data. Some class 'ids' have parameters in them. Note that the format is explained in the f.? functions.

Value

A character string that represents the class id of this frequency.

Examples

freq <- f.x.times.a.day(f.daily(c(2023,5,16)),13, 12)
freq_class_id <- get.class.id(freq) # this will be 'da13|d'.

Convert Frequency to Character and Class Id

Description

This function returns the output of the as.character.ldtf and get.class.id functions.

Usage

get.class.id0(frequency)

Arguments

Value

A list with the following items:

• value: The string representation of the frequency. If you only want this, use the as.character() function.

• day: The class Id of this frequency. If you only want this, use the get.class.id function.

• classType: The type of the class.

See Also

get.class.id

Examples

freq <- f.x.times.a.day(f.daily(c(2023,5,16)),13, 12)
freq_class_id <- get.class.id0(freq)

freq1 <- f.monthly(2020,3)
freq1_class_id <- get.class.id0(freq1)

Calculate Long-run Growth

Description

Use this function to calculate the long-run growth of a time-series data.

Usage

get.longrun.growth(
  data,
  continuous = FALSE,
  isPercentage = FALSE,
  trimStart = 0,
  trimEnd = 0,
  skipZero = TRUE
)

Arguments

Details

A variable can have discrete growth (y(t)=y(0) (1+g_1)(1+g_2)\ldots (1+g_t)) or continuous growth (y(t)=y(0)e^{g_1}e^{g_2}\ldots e^{g_t}) over t periods. y(0) is the first value and y(n) is the last value. By long-run growth rate, we mean a number such as g such that if we start from y(0) and the variable growth is g every period, we reach y(t) after t periods. This number summarizes all g_is, however, it is not generally the average of these rates.

Value

The long-run growth rate (percentage).

Examples

y <- c(60, 70, 80, 95)
g <- get.longrun.growth(y, isPercentage = TRUE, continuous = FALSE)
# Note that 'g' is different from 'mean(y)'.

Generate a Sequence from a Range of Frequencies

Description

Use this function to generate a list of character strings, where each element is a string representation of a frequency within the specified range.

Usage

get.seq(from, to, by = 1)

Arguments

Details

The two arguments from and to should be valid frequencies (see the f.? functions). They should also be consistent; you cannot create a sequence in which one is, for example, monthly and the other is yearly.

Value

A list of character strings that represents the sequence.

See Also

get.seq0

Examples

from <- f.monthly(2020,1)
to <- f.monthly(2021,12)
sequence1 <- get.seq(from, to, 1) # this will be '2020M1', '2020M2', ..., '2021M12'
sequence2 <- get.seq(from, to, 2) # this will be '2020M1', '2020M3', ..., '2021M11'
sequence3 <- get.seq(from, to, 3) # this will be '2020M1', '2020M4', ..., '2021M10'

# backward:
sequence4 <- get.seq(to, from, -1) # this will be '2021M12', '2021M11', ..., '2020M1'

Generate a Sequence from a Range of Frequencies

Description

Use this function to generate a list of character strings, where each element is a string representation of a frequency within the specified range.

Usage

get.seq0(start, length, by = 1)

Arguments

Value

A list of character strings that represents the sequence.

See Also

get.seq

Examples

start <- f.monthly(2020,1)
sequence1 <- get.seq0(start, 24, 1) # this will be '2020M1', '2020M2', ..., '2021M12'
sequence2 <- get.seq0(start, 24, 2) # this will be '2020M1', '2020M3', ..., '2023M11'
sequence3 <- get.seq0(start, 24, 3) # this will be '2020M1', '2020M4', ..., '2025M10'

# backward:
sequence4 <- get.seq0(start, 24, -1) # this will be '2020M1', '2019M12', ..., '2018M2'

# Lists are a little different:
start_l <- f.list.string(c("A","B","C","D"), "C")
sequence5 <- get.seq0(start_l, 5, 1) # this will be 'C', 'D', 'out_item:1', ..., 'out_item:3'

Get Length of Data in a Variable

Description

Get Length of Data in a Variable

Usage

## S3 method for class 'ldtv'
length(x)

Arguments

Value

Length of data in x.

Get Interval between two frequencies

Description

Use this function to get the number of intervals between two frequencies.

Usage

minus.freqs(freq1, freq2)

Arguments

Value

The number of intervals between the two frequencies (freq1 - freq2).

Examples

f1 <- f.yearly(2000)
f2 <- f.yearly(2010)
count <- minus.freqs(f1, f2) # this is -10
count <- minus.freqs(f2, f1) # this is 10

Get Next Frequency

Description

Use this function to get the next frequency.

Usage

next.freq(freq, count)

Arguments

Value

The next frequency after the given frequency.

Examples

f <- f.yearly(2000)
fn <- next.freq(f, 10) # this is 2010

Data for Vignette

Description

This is oil price data from 2010 retrieved by using the following code: oil_price <- Quandl::Quandl("OPEC/ORB", start_date="2010-01-01") It is saved due to the fact that CRAN checks may fail if the vignette relies on an external API call.

Usage

oil_price

Format

A data.frame with 2 columns: Date and Value

Print a Frequency

Description

Print a Frequency

Usage

## S3 method for class 'ldtf'
print(x, ...)

Arguments

Value

NULL

Print a Variable

Description

Use this to print a variable.

Usage

## S3 method for class 'ldtv'
print(x, ...)

Arguments

Value

NULL

Scenarios for Removing NAs

Description

Use this function to remove NA values from a matrix. This helps you to optimize the size of the information.

Usage

remove.na.strategies(
  data,
  countFun = function(nRows, nCols) nRows * nCols,
  rowIndices = NULL,
  colIndices = NULL,
  printMsg = FALSE
)

Arguments

Details

When a matrix has NA values, one can omit columns with NA, rows with NA, or a combination of these two. The total number of observations is a function of the order. This function tries all combinations and returns the results.

Value

A list of lists, each with the following elements:

Examples

data <- matrix(c(NA, 2, 3, 4, NA, 5, NA, 6, 7, NA, 9, 10, 11, 12, 13, 14, 15, NA, 16, 17), 4, 5)
res <- remove.na.strategies(data)

Get Row Names of a Variable

Description

Get Row Names of a Variable

Usage

## S3 method for class 'ldtv'
row.names(x)

Arguments

Value

A character string vector with frequencies of the observations as the row names.

Create a Variable

Description

Use this function to create a variable, which is a data array with frequencies. It can have a name and other named fields.

Usage

variable(data, startFrequency = NULL, name = NULL, fields = NULL)

Arguments

Value

An object of class ldtv, which is also a list with the following members:

• data: Determines the data.

• name: Determines the name.

• startFrequency: Determines the startFrequency.

• fields: Determines the fields.

Examples

data <- c(1,2,3,2,3,4,5)
start_f <- f.monthly(2022,12)
fields <- list(c("key1","value1"), c("key2", "value2"))
v1 = variable(data, start_f, "V1", fields)