initialise_commonfactorstructure_macropca {RCTS}

Initialises the estimation of the common factors and their loadings.

Description

This is a short version of initialise_commonfactorstructure() which only contains implementations for the robust macropca case and the classical case.

Usage

initialise_commonfactorstructure_macropca(
  Y,
  X,
  beta_est,
  g,
  factor_group,
  k,
  kg,
  robust,
  method_estimate_beta = "individual",
  method_estimate_factors = "macro",
  verbose = FALSE
)

Arguments

Y

Y: NxT dataframe with the panel data of interest

X

dataframe with the observed variables

beta_est

estimated values of beta

g

Vector with estimated group membership for all individuals

factor_group

estimated group specific factors

k

number of estimated common factors

kg

vector with the number of estimated group specific factors

robust

TRUE or FALSE: defines using the classical or robust algorithm to estimate beta

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".

method_estimate_factors

specifies the robust algorithm to estimate factors: default is "macro". The value is not used when robust is set to FALSE.

verbose

when TRUE, it prints messages

Value

list: 1st element contains the common factor(s) and the second element contains the factor loadings

Examples

set.seed(1)
original_data <- create_data_dgp2(30, 20)
Y <- original_data[[1]]
X <- original_data[[2]]
g <- original_data[[3]]
beta_est <- matrix(rnorm(4 * ncol(Y)), nrow = 4)
initialise_commonfactorstructure_macropca(Y, X, beta_est, g, NA, 0, c(3, 3, 3), TRUE)