assess_joint_sktest: Tests the skewness and kurtosis of a VAR model

In roqua/autovarCore: Automated Vector Autoregression Models and Networks

Description

This function tests the joint skewness and kurtosis for the residuals of the endogenous variables in the specified VAR model. This function uses an implementation equivalent to STATA's sktest. Of the p-levels resulting from assessing the significance of the joint sktest for the residuals of that variable, the minimum is returned.

Usage

assess_joint_sktest(varest)

Arguments

varest

A varest model.

Value

This function returns a p-level.

Examples

data_matrix <- matrix(nrow = 40, ncol = 3)
data_matrix[, ] <- runif(ncol(data_matrix) * nrow(data_matrix), 1, nrow(data_matrix))
colnames(data_matrix) <- c('rumination', 'happiness', 'activity')
varest <- autovarCore:::run_var(data_matrix, NULL, 1)
autovarCore:::assess_joint_sktest(varest)

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