assess_portmanteau: Tests the white noise assumption for a VAR model using a...

In autovarCore: Automated Vector Autoregression Models and Networks

Description

This function tests the white noise assumption for the residuals of the endogenous variables in the specified VAR model. This function implements the portmanteau test known as the Ljung-Box test, and results are comparable with STATA's wntestq. Of the p-levels resulting from assessing the white noise assumption for the residuals of that variable, the minimum is returned.

Usage

assess_portmanteau(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_portmanteau(varest)

Example output

[1] 0.3689733

autovarCore documentation built on May 2, 2019, 4:01 a.m.