data_prep: Introduction of time and section fixed effects and data...

In rmsBMA: Reduced Model Space Bayesian Model Averaging

Introduction of time and section fixed effects and data standardization.

Description

If the data is in the panel form the function assumes it has the following structure

section_1 year_1 y x1 x2 x3 ....
section_2 year_1 y x1 x2 x3 ....
section_3 year_1 y x1 x2 x3 ....
........
section_n year_1 y x1 x2 x3 ....
section_1 year_2 y x1 x2 x3 ....
section_2 year_2 y x1 x2 x3 ....
section_3 year_2 y x1 x2 x3 ....
........
section_n year_2 y x1 x2 x3 ....
........
section_n year_(T-1) y x1 x2 x3 ....
section_1 year_T y x1 x2 x3 ....
section_2 year_T y x1 x2 x3 ....
section_3 year_T y x1 x2 x3 ....
........
section_n year_T y x1 x2 x3 ....

Usage

data_prep(
  data,
  FE = FALSE,
  Time = 0,
  Section = 0,
  Time_FE = 0,
  Section_FE = 0,
  STD = 0
)

Arguments

data	A data file.
FE	Binary variable: TRUE - include fixed effect, FALSE - do not include fixed effects.
Time	The number of time periods - works only if FE=1.
Section	The number of cross-sections - works only if EF=1.
Time_FE	Binary variable: 1 - include time fixed effect, 0 - do not include time fixed effects. Works only if EF=1.
Section_FE	Binary variable: 1 - include cross-section fixed effect, 0 - do not include cross-section fixed effects. Works only if EF=1.
STD	Binary variable: 1 - standardize the data set, 0 - do not standardize the data set. By standardization we mean subtraction of a mean and division by standard deviation of each variable.

Value

Formatted data set.

Examples

y <- matrix(1:20,nrow=20,ncol=1)
x1 <- matrix(21:40,nrow=20,ncol=1)
x2 <- matrix(41:60,nrow=20,ncol=1)
data <- cbind(y,x1,x2)
new_data <- data_prep(data,FE=1,Time=5,Section=4,Time_FE=1,Section_FE=1,STD=0)

y <- rnorm(20, mean = 0, sd = 1)
x1 <- rnorm(20, mean = 0, sd = 1)
x2 <- rnorm(20, mean = 0, sd = 1)
data <- cbind(y,x1,x2)
new_data <- data_prep(data,FE=1,Time=5,Section=4,Time_FE=1,Section_FE=1,STD=1)

rmsBMA documentation built on March 14, 2026, 5:06 p.m.