transformData: Transform data to make it stationary

In sparseDFM: Estimate Dynamic Factor Models with Sparse Loadings

Transform data to make it stationary

Description

Methods to transform the data to make it stationary. Input a n \times p numeric data matrix and what transform is required for each data series. Returns a n \times p matrix of the transformed data.

Usage

transformData(X, stationary_transform)

Arguments

X

n x p numeric data matrix

stationary_transform

p-dimensional vector filled with numbers from \{1,2,3,4,5,6,7\} representing: 1 no change 2 first difference X_{i,t} - X_{i,t-1} 3 second difference (X_{i,t} - X_{i,t-1}) - (X_{i,t-1} - X_{i,t-2}) 4 log first difference log(X_{i,t}) - log(X_{i,t-1}) 5 log second difference (log(X_{i,t}) - log(X_{i,t-1})) - (log(X_{i,t-1}) - log(X_{i,t-2})) 6 growth rate (X_{i,t} - X_{i,t-1})/X_{i,t-1} 7 log growth rate (log(X_{i,t}) - log(X_{i,t-1}))/log(X_{i,t-1})

Value

Transformed stationary version of \bm{X}.

sparseDFM documentation built on March 31, 2023, 10:15 p.m.