needs_trend: Determines if a trend is required for the specified VAR model

In roqua/autovarCore: Automated Vector Autoregression Models and Networks

Description

This function uses the Phillips-Perron Unit Root Test to determine whether a trend is required for a VAR model based on the given matrix of endogenous variables and the given lag. All variables are assessed individually. This function returns TRUE if any of the endogenous variables requires a trend.

Usage

needs_trend(endo_matrix, lag)

Arguments

endo_matrix	The matrix of endogenous variables in the model.
lag	An integer specifying the lag length of the model.

Value

A boolean indicating whether a trend is required for the specified VAR model.

Examples

data_matrix <- matrix(nrow = 40, ncol = 3)
data_matrix[, ] <- runif(ncol(data_matrix) * nrow(data_matrix), 1, 10)
data_matrix[, 3] <- (1:40) + rnorm(40)
colnames(data_matrix) <- c('rumination', 'happiness', 'activity')
data_matrix
autovarCore:::needs_trend(data_matrix, 1)

roqua/autovarCore documentation built on Oct. 12, 2020, 4:16 a.m.