mglm4twin: Fitting Multivariate Covariance Generalized Linear Models to...

In wbonat/mglm4twin: Multivariate Generalized linear Models for Twin Data

Fitting Multivariate Covariance Generalized Linear Models to Twin data

Description

The function mglm4twin is used for fitting multivariate generalized linear models to twin data. 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 and variance functions. The models are fitted using an estimating function approach, combining the quasi-score function for the regression parameters and the Pearson estimating function for the covariance parameters. For details see Bonat and Jorgensen (2016).

Usage

mglm4twin(linear_pred, matrix_pred, link, variance,
       offset, Ntrial, power_fixed, weights, data, control_initial,
       contrasts, control_algorithm)

Arguments

linear_pred	a list of formula see formula for details.
matrix_pred	a list of matrices, in general the output of mt_twin function.
link	a list of link functions names. Options are: "logit", "probit", "cauchit", "cloglog", "loglog", "identity", "log", "sqrt", "1/mu^2" and "inverse". See mt_link_function for details.
variance	a list of variance functions names. Options are: "constant", "tweedie", "poisson_tweedie", "binomialP" and "binomialPQ". See mt_variance_function for details.
offset	a list of offset values if any.
Ntrial	a list of number of trials on Bernoulli experiments. It is useful only for binomialP and binomialPQ variance functions.
power_fixed	a list of logicals indicating if the values of the power parameter should be estimated or not.
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.
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 mt_initial_values.
contrasts	extra arguments to passed to model.matrix.
control_algorithm	a list of arguments to be passed for the fitting algorithm. See fit_mglm for details.

Value

mcglm returns an object of class 'mcglm'.

Author(s)

Wagner Hugo Bonat, [e-mail]

Source

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.

See Also

fit_mglm, mt_link_function and mt_variance_function.

wbonat/mglm4twin documentation built on Oct. 14, 2023, 9:37 p.m.