run_tests: Execute a series of model validity assumptions

Description Usage Arguments Value Examples

Description

This function returns the given suite of tests on for the given VAR model. For each test, the result is the minimum p-level of all the assumptions and p-levels checked within the test. In other words, the result of a test is the p-level that should be used as a threshold below which outcomes are considered statistically significant (e.g., a result of 0.06 is better than a result of 0.03). The run_tests function returns a vector of results, one for each test, in the order corresponding to the test_names argument.

Usage

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run_tests(varest, test_names)

Arguments

varest

A varest model.

test_names

A vector of names of tests given as character strings. Supported tests are specified in the autovarCore:::supported_test_names() function.

Value

This function returns a vector of p-levels.

Examples

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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:::run_tests(varest, 'portmanteau')

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