Fitting multivariate covariance generalized linear models (McGLMs) to data. McGLMs is a general framework for non-normal multivariate data analysis, designed to handle multivariate response variables, along with a wide range of temporal and spatial correlation structures defined in terms of a covariance link function combined with a matrix linear predictor involving known matrices. The models take non-normality into account in the conventional way by means of a variance function, and the mean structure is modelled by means of a link function and a linear predictor. The models are fitted using an efficient Newton scoring algorithm based on quasi-likelihood and Pearson estimating functions, using only second-moment assumptions. This provides a unified approach to a wide variety of different types of response variables and covariance structures, including multivariate extensions of repeated measures, time series, longitudinal, spatial and spatio-temporal structures. The package offers a user-friendly interface for fitting McGLMs similar to the glm() R function.
|Author||Wagner Hugo Bonat [aut, cre], Walmes Marques Zeviani [ctb], Fernando de Pol Mayer [ctb]|
|Date of publication||2016-06-09 20:23:56|
|Maintainer||Wagner Hugo Bonat <firstname.lastname@example.org>|
|License||GPL-3 | file LICENSE|
ahs: Australian Health Survey
anova.mcglm: Anova Tables
coef.mcglm: Model Coefficients
confint.mcglm: Confidence Intervals for Model Parameters
covprod: Cross variability matrix
ESS: Generalized Error Sum of Squares
fit_mcglm: Chaser and Reciprocal Likelihood Algorithms
fitted.mcglm: Fitted Values
gof: Measures of Goodness-of-Fit
GOSHO: Gosho Information Criterion
Hunting: Hunting in Pico Basile, Bioko Island, Equatorial Guinea.
mc_bias_corrected_std: Bias-corrected Standard Error for Regression Parameters
mc_build_bdiag: Build a block-diagonal matrix of zeros.
mc_build_C: Build the joint covariance matrix
mc_build_omega: Build omega matrix
mc_build_sigma: Build variance-covariance matrix
mc_build_sigma_between: Build the correlation matrix between response variables
mc_car: Conditional Autoregressive Model Structure
mc_compute_rho: Autocorrelation Estimates
mc_conditional_test: Conditional Hypotheses Tests
mc_core_pearson: Core of the Pearson estimating function.
mc_correction: Pearson correction term
mc_cross_variability: Compute the cross-variability matrix
mc_derivative_cholesky: Derivatives of the Cholesky decomposition
mc_derivative_C_rho: Derivative of C with respect to rho.
mc_derivative_expm: Derivative of exponential-matrix function
mc_derivative_sigma_beta: Derivatives of V^1/2 with respect to beta.
mc_dexp_gold: Exponential-matrix and its derivatives
mc_dist: Distance Models Structure
mc_expm: Exponential-matrix covariance link function
mc_getInformation: Getting information about model parameters
mcglm: Fitting Multivariate Covariance Generalized Linear Models
mc_id: Independent Model Structure
mc_initial_values: Automatic Initial Values
mc_link_function: Link Functions
mc_list2vec: Auxiliar function transforms list to a vector.
mc_ma: Moving Average Models Structure
mc_matrix_linear_predictor: Matrix Linear Predictor
mc_mixed: Mixed Models Structure
mc_pearson: Pearson estimating function
mc_quasi_score: Quasi-score function
mc_robust_std: Robust Standard Error for Regression Parameters
mc_rw: Random Walk Models Structure
mc_sandwich: Matrix product in sandwich form
mc_sensitivity: Sensitivity matrix
mc_sic: Score Information Criterion - Regression
mc_sic_covariance: Score Information Criterion - Covariance
mc_transform_list_bdiag: Auxiliar function to compute the derivatives of the C matrix.
mc_updateBeta: Updated regression parameters
mc_updateCov: Updated covariance parameters
mc_variability: Variability matrix
mc_variance_function: Variance Functions
NewBorn: Respiratory Physiotherapy on Premature Newborns.
pAIC: Pseudo Akaike Information Criterion
pKLIC: Pseudo Kullback-Leibler Information Criterion
plogLik: Gaussian Pseudo-loglikelihood
plot.mcglm: Residuals and algorithm check plots
RJC: Rotnitzky-Jewell Information Criterion
soil: Soil Chemistry Properties Data
vcov.mcglm: Variance-Covariance Matrix