Given an lm object, this function computes the global and
directional test statistics for assessing the linear model assumptions.
computegvlma(lmobj, alphalevel, v)A linear models object resulting from a call to lm.
Level of significance to conduct tests for assessing the linear models assumptions.
The time sequence vector for the heteroscedasticity test, \(S^2_4\). A vector of length the number of observations in the linear model.
A gvlma object, which consists of the components of the linear models object provided as input, plus a list of the results of the model assumptions tests. The components associated with the global and directional tests are the following:
Significance level at which decisions (whether model assumptions are satisfied) were determined.
A list of the Value, pvalue and
Decision associated with the global test.
A list of the Value, pvalue and
Decision associated with the skewness directional test,
\(S^2_1\).
A list of the Value, pvalue and
Decision associated with the kurtosis directional test,
\(S^2_2\).
A list of the Value, pvalue and
Decision associated with the link function directional test,
\(S^2_3\).
A list of the Value, pvalue and
Decision associated with the heteroscedasticity test,
\(S^2_4\).
The time sequence used for the 4th directional statistic.
This function is not really meant to be called directly, but rather
by the function gvlma.
Pena, EA and Slate, EH (2006). “Global validation of linear model assumptions,” J.\ Amer.\ Statist.\ Assoc., 101(473):341-354.