prune_data: Obtain a balanced and possibly imputed and standardized panel...
In juhokalle/rmfd4dfm: Estimation of DFMs using RMFD-E parametrization

prune_data

R Documentation

Obtain a balanced and possibly imputed and standardized panel of data

This convenience function allows the user to manipulate the supplied data matrix with respect to

prune_data(
  df,
  int_vars = NULL,
  start_date = NULL,
  end_date = NULL,
  impute = TRUE,
  sdize = TRUE,
  trans_ix = NULL
)

`df`	`T x (N+1)` data panel with the first column specifying the time stamp, `T` giving the number of observations and `N` the number of variables
`int_vars`	vector of strings specifying the variables of interest, which are ordered first
`start_date`	ymd object specifying the start date of the sample
`end_date`	ymd object specifying the end date of the sample
`impute`	Are the outliers removed and replaced with an imputed value (for the imputation scheme see tw_apc)? Defaults to TRUE
`sdize`	Are the variables standardized to have zero mean and unit standard deviation? Defaults to FALSE
`trans_ix`	vector containing the transformation codes of the variables

list of components

`df`	A `T x N` data frame corresponding transformed data
`date`	vector of ymd components giving the sample span
`discarded`	A list of discarded variables containing missing values
`sd_mat`	If `sdize = TRUE`, a matrix containing standard deviations of the variables on the diagonal is also supplied
`trans_ix`	vector of reordered transformation codes if `int_vars` is supplied