unstack_tsDF {gseries} | R Documentation |
Reciprocal function of stack_tsDF()
Description
(version française: https://StatCan.github.io/gensol-gseries/fr/reference/unstack_tsDF.html)
Convert a stacked (tall) multivariate time series data frame (benchmarking()
and stock_benchmarking()
data format) into a non-stacked (wide) multivariate time series data frame.
This function, combined with tsDF_to_ts()
, is useful to convert the benchmarked data frame returned by a call to
benchmarking()
or stock_benchmarking()
back into a "mts" object, where multiple series were benchmarked in
BY-group processing mode.
Usage
unstack_tsDF(
ts_df,
ser_cName = "series",
yr_cName = "year",
per_cName = "period",
val_cName = "value"
)
Arguments
ts_df |
(mandatory) Data frame (object of class "data.frame") that contains the multivariate time series data to be unstacked. |
ser_cName |
(optional) String specifying the name of the character variable (column) in the input time series data frame that contains the series identifier (the time series variable names in the output data frame). Default value is |
yr_cName , per_cName |
(optional) Strings specifying the name of the numeric variables (columns) in the input time series data frame that contain the data point year and period identifiers. These variables are transferred to the output data frame with the same names. Default values are |
val_cName |
(optional) String specifying the name of the numeric variable (column) in the input time series data frame that contains the data point values. Default value is |
Value
The function returns a data frame with three or more variables:
Data point year, type numeric (see argument
yr_cName
)Data point period, type numeric (see argument
per_cName
)One time series data variable for each distinct value of the input data frame variable specified with argument
ser_cName
, type numeric (see argumentsser_cName
andval_cName
)
Note: the function returns a "data.frame" object than can be explicitly coerced to another type of object
with the appropriate as*()
function (e.g., tibble::as_tibble()
would coerce it to a tibble).
See Also
stack_tsDF()
tsDF_to_ts()
benchmarking()
stock_benchmarking()
Examples
# Proportional benchmarking for multiple (3) quarterly series processed with
# argument `by` (in BY-group mode)
ind_vec <- c(1.9, 2.4, 3.1, 2.2, 2.0, 2.6, 3.4, 2.4, 2.3)
ind_df <- ts_to_tsDF(ts(data.frame(ser1 = ind_vec,
ser2 = ind_vec * 100,
ser3 = ind_vec * 10),
start = c(2015, 1), frequency = 4))
bmk_vec <- c(10.3, 10.2)
bmk_df <- ts_to_bmkDF(ts(data.frame(ser1 = bmk_vec,
ser2 = bmk_vec * 100,
ser3 = bmk_vec * 10),
start = 2015, frequency = 1),
ind_frequency = 4)
out_bench <- benchmarking(stack_tsDF(ind_df),
stack_bmkDF(bmk_df),
rho = 0.729, lambda = 1, biasOption = 3,
by = "series",
quiet = TRUE)
# Initial and final (benchmarked) quarterly time series data frames
ind_df
unstack_tsDF(out_bench$series)