Internal functions used for model fit.
mclogit.fit.RdThese functions are exported and documented for use by other packages. They are not intended for end users.
Usage
mclogit.fit(y, s, w, X,
dispersion=FALSE,
start = NULL, offset = NULL,
control = mclogit.control(),
groups=NULL)
mmclogit.fitPQLMQL(y, s, w, X, Z, d,
start = NULL,
start.Phi = NULL,
start.b = NULL,
offset = NULL, method=c("PQL","MQL"),
estimator = c("ML","REML"),
control = mmclogit.control())Arguments
- y
a response vector. Should be binary.
- s
a vector identifying individuals or covariate strata
- w
a vector with observation weights.
- X
a model matrix; required.
- dispersion
a logical value or a character string; whether and how a dispersion parameter should be estimated. For details see
dispersion.- groups
a vector that identifies the groups relevant for the estimation of the dispersion parameter.
- Z
the random effects design matrix.
- d
dimension of random effects. Typically $d=1$ for random intercepts only, $d>1$ for models with random intercepts.
- start
an optional numerical vector of starting values for the coefficients.
- offset
an optional model offset. Currently only supported for models without random effects.
- start.Phi
an optional matrix of strarting values for the (co-)variance parameters.
- start.b
an optional list of vectors with starting values for the random effects.
- method
a character string, either "PQL" or "MQL", specifies the type of the quasilikelihood approximation.
- estimator
a character string; either "ML" or "REML", specifies which estimator is to be used/approximated.
- control
a list of parameters for the fitting process. See
mclogit.control