gvlma {gvlma} | R Documentation |
Top-level function for Global Validation of Linear Models Assumptions.
gvlma(x, data, alphalevel = 0.05, timeseq, ...) gvlma.form(formula, data, alphalevel = 0.05, timeseq = 1:nrow(data), ...) gvlma.lm(lmobj, alphalevel = 0.05, timeseq)
x |
Either a formula, in which case gvlma.form will be
called, or a linear models object, in which case gvlma.lm
will be invoked. |
formula |
A linear models formula interpretable within the
dataframe data . Should have a single reponse variable. |
lmobj |
An object resulting from a call to lm . |
data |
Required if x is a formula, ignored if x is
an lm object. A dataframe in which the variables in the formula
x can be interpreted. |
alphalevel |
Level of significance at which to perform the global and directional tests for linear models assumptions. |
timeseq |
A vector of length the number of observations in the linear model that gives a "time ordering" for the observations. This time sequence is used in the heteroscedasticity test statistic. Defaults to 1:n where n is the number of observations in the linear model. |
... |
Additional arguments such as subset that are
passed on to the call to
lm when x is a formula. Note that weights , while
being passed on to the call to lm , will not be used in any
special way in the gvlma computations. |
gvlma
is the top-level function to create a gvlma
object
for assessment of linear models assumptions.
A gvlma
object is returned. This is a list of class
“gvlma” that contains all of the components returned by the call to
lm
for fitting the linear model, plus an additional component
entitled “GlobalTest.” This new GlobalTest
component is a list with
the following components:
LevelOfSignificance |
The level of significance at which the decisions reported for the global and directional tests were made. |
GlobalStat4 |
A list consisting of the components Value ,
pvalue and Decision containing the global test statistic value,
associated p-value, and text phrase reporting the decision
concerning appropriateness of the linear model assumptions. |
DirectionalStat1 |
A list consisting of the Value ,
pvalue and Decision associated with the skewness
directional test statistic. |
DirectionalStat2 |
A list consisting of the Value ,
pvalue and Decision associated with the kurtosis
directional test statistic. |
DirectionalStat3 |
A list consisting of the Value ,
pvalue and Decision associated with the link function
directional test statistic. |
DirectionalStat4 |
A list consisting of the Value ,
pvalue and Decision associated with the heteroscedasticity
directional test statistic. |
timeseq |
The ordering of the observations used when computing the heteroscedasticity directional statistic. |
call |
The call used to invoke gvlma . |
Slate, EH SlateEH@musc.edu and Pena, EA pena@stat.sc.edu.
Pena, EA and Slate, EH (2006). “Global validation of linear model assumptions,” J. Amer. Statist. Assoc., 101(473):341-354.
plot.gvlma
, deletion.gvlma
,
update.gvlma
,
lm
data(CarMileageData) CarModelAssess <- gvlma(NumGallons ~ MilesLastFill + NumDaysBetw, data = CarMileageData) CarModelAssess summary(CarModelAssess) CarModel2 <- gvlma(lm(NumGallons ~ MilesLastFill + NumDaysBetw, data = CarMileageData)) CarModel2 summary(CarModel2) plot(CarModel2)