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logLik
extracts the log-likelihood (exact or approximated).
fitted
extracts fitted values (see fitted.values
).
fixef
extracts the fixed effects coefficients, $\beta$.
ranef
extracts the predicted random effects, $u$.
vcov
returns the variance-covariance matrix of the fixed-effects coefficients.
predictionCoeffs
precomputes coefficients for prediction (see predict
for an example)## S3 method for class 'HLfit':
logLik(object,REML,...)
## S3 method for class 'HLfit':
fitted(object,...)
## S3 method for class 'HLfit':
fixef(object,...)## S3 method for class 'HLfit':
ranef(object,...)
## S3 method for class 'HLfit':
vcov(object,...)
predictionCoeffs(object)
TRUE
, the function returns the log restricted likelihood (exact or approximated).logLik
) or vectors (most cases) or matrices (for vcov
). ranef
returns a vector with attributes,
which inherits from class ranef
which has its own (undocumented) print
method.data(wafers)
m1 <- HLfit(y ~X1+X2+(1|batch),
resid.formula = ~ 1 ,data=wafers,HLmethod="ML")
fixef(m1)
vcov(m1)
ranef(m1)
## see 'predict' for a example with predictionCoeffs
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