The function mcglm
is used to fit multivariate
covariance generalized linear models.
The models are specified by a set of lists giving a symbolic
description of the linear and matrix linear predictors.
The user can choose between a list of link, variance and covariance
functions. The models are fitted using an estimating function
approach, combining quasi-score functions for regression
parameters and Pearson estimating function for covariance
parameters. For details see Bonat and Jorgensen (2016).
mcglm(linear_pred, matrix_pred, link, variance, covariance, offset, Ntrial, power_fixed, data, control_initial, contrasts, weights, control_algorithm)
linear_pred | a list of formula see |
---|---|
matrix_pred | a list of known matrices to be used on the matrix
linear predictor. For details see
|
link | a list of link functions names. Options are:
|
variance | a list of variance functions names.
Options are: |
covariance | a list of covariance link functions names.
Options are: |
offset | a list of offset values if any. |
Ntrial | a list of number of trials on Bernoulli
experiments. It is useful only for |
power_fixed | a list of logicals indicating if the values of the power parameter should be estimated or not. |
data | a data frame. |
control_initial | a list of initial values for the fitting
algorithm. If no values are supplied automatic initial values
will be provided by the function |
contrasts | extra arguments to passed to
|
weights | A list of weights for model fitting. Each element of the list should be a vector of weights of size equals the number of observations. Missing observations should be annotated as NA. |
control_algorithm | a list of arguments to be passed for the
fitting algorithm. See |
Bonat, W. H. and Jorgensen, B. (2016) Multivariate covariance generalized linear models. Journal of Royal Statistical Society - Series C 65:649--675.
Bonat, W. H. (2018). Multiple Response Variables Regression Models in R: The mcglm Package. Journal of Statistical Software, 84(4):1--30.
mcglm returns an object of class 'mcglm'.
fit_mcglm
, mc_link_function
and
mc_variance_function
.