mcglm: Multivariate Covariance Generalized Linear Models

Share:

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 <wbonat@ufpr.br>
License
GPL-3 | file LICENSE
Version
0.3.0
URLs

View on CRAN

Man pages

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_sensitivity
Cross-sensitivity
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
print.mcglm
Print
residuals.mcglm
Residuals
RJC
Rotnitzky-Jewell Information Criterion
soil
Soil Chemistry Properties Data
soya
Soybeans
summary.mcglm
Summarizing
vcov.mcglm
Variance-Covariance Matrix

Files in this package

mcglm
mcglm/inst
mcglm/inst/doc
mcglm/inst/doc/vignette-01.html
mcglm/inst/doc/GLMExamples.html
mcglm/inst/doc/GLMExamples.R
mcglm/inst/doc/UniModels.R
mcglm/inst/doc/vignette-01.Rmd
mcglm/inst/doc/vignette-01.R
mcglm/inst/doc/GLMExamples.Rmd
mcglm/inst/doc/UniModels.Rmd
mcglm/inst/doc/UniModels.html
mcglm/tests
mcglm/tests/testthat.R
mcglm/tests/testthat
mcglm/tests/testthat/test_mc_build_sigma_between.R
mcglm/tests/testthat/test_mc_link_function.R
mcglm/tests/testthat/test_mc_matrix_linear_predictor.R
mcglm/tests/testthat/test_mc_build_C.R
mcglm/tests/testthat/test_mc_build_omega.R
mcglm/tests/testthat/test_mc_build_sigma.R
mcglm/tests/testthat/test_mc_variance_function.R
mcglm/tests/testthat/test_mc_quasi_score.R
mcglm/NAMESPACE
mcglm/data
mcglm/data/NewBorn.RData
mcglm/data/soya.RData
mcglm/data/ahs.RData
mcglm/data/Hunting.RData
mcglm/data/soil.RData
mcglm/R
mcglm/R/mc_cross_sensitivity.R
mcglm/R/mc_pearson.R
mcglm/R/mc_transform_list_bdiag.R
mcglm/R/mc_getInformation.R
mcglm/R/mc_variability.R
mcglm/R/mc_cross_variability.R
mcglm/R/mc_conditional_test.R
mcglm/R/mc_compute_rho.R
mcglm/R/mc_correction.R
mcglm/R/mc_build_bdiag.R
mcglm/R/mc_build_omega.R
mcglm/R/zzz_onAttach.R
mcglm/R/mc_derivative_expm.R
mcglm/R/mc_build_C.R
mcglm/R/mc_id.R
mcglm/R/mc_dexp_gold.R
mcglm/R/mcglm.R
mcglm/R/mc_pAIC.R
mcglm/R/mc_KLIC.R
mcglm/R/mc_S3_methods.R
mcglm/R/mc_derivative_C_rho.R
mcglm/R/mc_dist.R
mcglm/R/mc_derivative_cholesky.R
mcglm/R/mc_ma.R
mcglm/R/mc_plogLik.R
mcglm/R/mc_main_function.R
mcglm/R/mc_sic_covariance.R
mcglm/R/mc_car.R
mcglm/R/mc_ess.R
mcglm/R/mc_rw.R
mcglm/R/mc_initial_values.R
mcglm/R/mc_updatedCov.R
mcglm/R/mc_RJC.R
mcglm/R/mc_bias_correct_std.R
mcglm/R/mc_matrix_linear_predictor.R
mcglm/R/mc_robust_std.R
mcglm/R/mc_auxiliar.R
mcglm/R/mc_core_pearson.R
mcglm/R/mc_gosho.R
mcglm/R/mc_sensitivity.R
mcglm/R/mc_dexpm.R
mcglm/R/mc_build_sigma.R
mcglm/R/mc_core_cross_variability.R
mcglm/R/mc_sic.R
mcglm/R/mc_gof.R
mcglm/R/fit_mcglm.R
mcglm/R/mc_derivative_sigma_beta.R
mcglm/R/mc_list2vec.R
mcglm/R/mc_variance_function.R
mcglm/R/mc_updatedBeta.R
mcglm/R/mc_build_sigmab.R
mcglm/R/mc_quasi_score.R
mcglm/R/mc_link_function.R
mcglm/R/mc_mixed.R
mcglm/vignettes
mcglm/vignettes/_output.yaml
mcglm/vignettes/vignette-01.Rmd
mcglm/vignettes/GLMExamples.Rmd
mcglm/vignettes/UniModels.Rmd
mcglm/vignettes/style.css
mcglm/vignettes/MathJax.html
mcglm/MD5
mcglm/build
mcglm/build/vignette.rds
mcglm/DESCRIPTION
mcglm/man
mcglm/man/mc_bias_corrected_std.Rd
mcglm/man/mc_sic.Rd
mcglm/man/mc_link_function.Rd
mcglm/man/plogLik.Rd
mcglm/man/mc_sandwich.Rd
mcglm/man/mc_core_pearson.Rd
mcglm/man/soya.Rd
mcglm/man/mc_robust_std.Rd
mcglm/man/NewBorn.Rd
mcglm/man/covprod.Rd
mcglm/man/confint.mcglm.Rd
mcglm/man/mc_compute_rho.Rd
mcglm/man/mc_dexp_gold.Rd
mcglm/man/mc_expm.Rd
mcglm/man/mc_id.Rd
mcglm/man/mc_quasi_score.Rd
mcglm/man/mc_ma.Rd
mcglm/man/mc_build_sigma_between.Rd
mcglm/man/mc_derivative_expm.Rd
mcglm/man/GOSHO.Rd
mcglm/man/mc_build_sigma.Rd
mcglm/man/mc_cross_variability.Rd
mcglm/man/mc_list2vec.Rd
mcglm/man/mc_car.Rd
mcglm/man/mc_matrix_linear_predictor.Rd
mcglm/man/summary.mcglm.Rd
mcglm/man/mc_cross_sensitivity.Rd
mcglm/man/print.mcglm.Rd
mcglm/man/mc_variability.Rd
mcglm/man/mc_mixed.Rd
mcglm/man/mc_build_bdiag.Rd
mcglm/man/mc_updateCov.Rd
mcglm/man/mc_sic_covariance.Rd
mcglm/man/pAIC.Rd
mcglm/man/mc_derivative_cholesky.Rd
mcglm/man/mc_build_C.Rd
mcglm/man/mc_derivative_sigma_beta.Rd
mcglm/man/mc_rw.Rd
mcglm/man/mcglm.Rd
mcglm/man/mc_transform_list_bdiag.Rd
mcglm/man/mc_correction.Rd
mcglm/man/vcov.mcglm.Rd
mcglm/man/mc_build_omega.Rd
mcglm/man/mc_derivative_C_rho.Rd
mcglm/man/ESS.Rd
mcglm/man/soil.Rd
mcglm/man/mc_getInformation.Rd
mcglm/man/Hunting.Rd
mcglm/man/mc_initial_values.Rd
mcglm/man/mc_pearson.Rd
mcglm/man/mc_sensitivity.Rd
mcglm/man/pKLIC.Rd
mcglm/man/plot.mcglm.Rd
mcglm/man/RJC.Rd
mcglm/man/ahs.Rd
mcglm/man/fit_mcglm.Rd
mcglm/man/mc_conditional_test.Rd
mcglm/man/fitted.mcglm.Rd
mcglm/man/coef.mcglm.Rd
mcglm/man/residuals.mcglm.Rd
mcglm/man/mc_updateBeta.Rd
mcglm/man/mc_variance_function.Rd
mcglm/man/anova.mcglm.Rd
mcglm/man/mc_dist.Rd
mcglm/man/gof.Rd
mcglm/LICENSE