grid_add_variables: Function which is used to have a dataframe (called "grid")...

In eh-in-r/RCTS: Clustering Time Series While Resisting Outliers

Function which is used to have a dataframe (called "grid") with data (individualindex, timeindex, XT and LF) available.

Description

It is used in iterate().

Usage

grid_add_variables(
  grid,
  Y,
  X,
  beta_est,
  g,
  lambda,
  comfactor,
  method_estimate_beta,
  vars_est,
  S,
  limit_est_groups_heterogroups = 15
)

Arguments

grid	dataframe containing values for X*beta_est and LF (product of common factor and its loadings)
Y	Y: NxT dataframe with the panel data of interest
X	X: NxTxp array containing the observable variables
beta_est	estimated values of beta
g	Vector with estimated group membership for all individuals
lambda	loadings of the estimated common factors
comfactor	estimated common factors
method_estimate_beta	defines how beta is estimated. Default case is an estimated beta for each individual. Default value is "individual." Possible values are "homogeneous", "group" or "individual".
vars_est	number of variables that will be included in the algorithm and have their coefficient estimated. This is usually equal to the number of observable variables.
S	number of estimated groups
limit_est_groups_heterogroups	maximum amount of groups that can be estimated when method_estimate_beta is set to "group"

Value

data.frame

eh-in-r/RCTS documentation built on May 19, 2023, 1:09 p.m.