avm.fwls | R Documentation |
This function applies feasible weighted least squares (FWLS) to a
linear regression model using error variance estimates obtained
from an auxiliary linear variance model fit using alvm.fit
or from an auxiliary nonlinear variance model fit using
anlvm.fit
.
avm.fwls(object, fastfit = FALSE)
object |
Either an object of class |
fastfit |
A logical. If |
The function simply calculates
\hat{β}=(X'\hat{Ω}^{-1}X)^{-1}X'\hat{Ω}^{-1}y
, where X is the design matrix, y is the response vector, and \hat{Ω} is the diagonal variance-covariance matrix of the random errors, whose diagonal elements have been estimated by an auxiliary variance model.
Either an object of class
"lm"
(if fastfit
is FALSE
) or otherwise a generic
list object
alvm.fit
, anlvm.fit
,
avm.vcov
mtcars_lm <- lm(mpg ~ wt + qsec + am, data = mtcars) myalvm <- alvm.fit(mainlm = mtcars_lm, model = "linear", varselect = "qgcv.linear") myfwls <- avm.fwls(myalvm) cbind(coef(mtcars_lm), coef(myfwls))
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