calculate_virtual_factor_and_lambda_group {RCTS}

Helpfunction used in update_g()

Description

This function calculates FgLg (the groupfactorstructure) for all possible groups where individual i can be placed. For each group were the groupfactors (Fg) estimated earlier. Now the grouploadings are needed for each group as well. In the classical case these are calculated by Fg*Y/T. In the robust case these are robust.

Usage

calculate_virtual_factor_and_lambda_group(
  group,
  solve_FG_FG_times_FG,
  robust,
  NN_local,
  method_estimate_factors_local,
  g,
  vars_est,
  number_of_group_factors_local,
  number_of_common_factors_local,
  method_estimate_beta,
  factor_group,
  lambda,
  comfactor,
  Y,
  X,
  beta_est,
  verbose = FALSE
)

Arguments

group

number of groups

solve_FG_FG_times_FG

This is the same as groupfactor / T. It is only used in the Classical approach

robust

robust or classical estimation of group membership

NN_local

number of time series

method_estimate_factors_local

specifies the robust algorithm to estimate factors: default is "macro"

g

vector with estimated group membership for all individuals

vars_est

number of variables that are included in the algorithm and have their coefficient estimated. This is usually equal to vars.

number_of_group_factors_local

number of group factors to be estimated

number_of_common_factors_local

number of common factors to be estimated

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".

factor_group

estimated group specific factors

lambda

loadings of the estimated common factors

comfactor

estimated common factors

Y

Y: NxT dataframe with the panel data of interest

X

X: NxTxp array containing the observable variables

beta_est

estimated values of beta

verbose

when TRUE, it prints messages

Value

NxT matrix containing the product of virtual groupfactors and virtual loadings