Internal functions used for model fit.
These functions are exported and documented for use by other packages. They are not intended for end users.
mclogit.fit(y, s, w, X,
dispersion=FALSE,
start = NULL, offset = NULL,
control = mclogit.control())
mmclogit.fitPQLMQL(y, s, w, X, Z, d, start,
offset = NULL, method=c("PQL","MQL"),
estimator = c("ML","REML"),
control = mmclogit.control())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 |
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. |
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 |
A list with components describing the fitted model.
Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.