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mcglm
View on CRAN: Click
here
Download and install mcglm package within the R console
Install from CRAN:
install.packages("mcglm")
Install from Github:
library("remotes")
install_github("cran/mcglm")
Install by package version:
library("remotes")
install_version("mcglm", "0.8.0")
Attach the package and use:
library("mcglm")
Maintained by
Wagner Hugo Bonat
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
First Published: 2016-06-09
Latest Update: 2023-08-25
Description:
Fitting multivariate covariance generalized linear
models (McGLMs) to data. McGLM 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.
See Bonat (2018) , for more information
and examples.
How to cite:
Wagner Hugo Bonat (2016). mcglm: Multivariate Covariance Generalized Linear Models. R package version 0.8.0, https://cran.r-project.org/web/packages/mcglm. Accessed 28 Mar. 2025.
Previous versions and publish date:
Other packages that cited mcglm R package
View mcglm citation profile
Other R packages that mcglm depends,
imports, suggests or enhances
Functions, R codes and Examples using
the mcglm R package
Some associated functions: ESS . GOSHO . Hunting . NewBorn . RJC . ahs . anova.mcglm . coef.mcglm . confint.mcglm . covprod . fit_mcglm . fitted.mcglm . gof . mc_anova_disp . mc_bias_corrected_std . mc_build_C . mc_build_F . mc_build_bdiag . mc_build_omega . mc_build_sigma . mc_build_sigma_between . mc_car . mc_complete_data . mc_compute_rho . mc_conditional_test . mc_core_pearson . mc_correction . mc_cross_sensitivity . mc_cross_variability . mc_derivative_C_rho . mc_derivative_cholesky . mc_derivative_expm . mc_derivative_sigma_beta . mc_dexp_gold . mc_dglm . mc_dist . mc_expm . mc_getInformation . mc_id . mc_initial_values . mc_link_function . mc_list2vec . mc_ma . mc_manova . mc_manova_disp . mc_matrix_linear_predictor . mc_mixed . mc_ns . mc_pearson . mc_quasi_score . mc_remove_na . mc_robust_std . mc_rw . mc_sandwich . mc_sensitivity . mc_sic . mc_sic_covariance . mc_transform_list_bdiag . mc_twin . mc_updateBeta . mc_updateCov . mc_variability . mc_variance_function . mcglm . pAIC . pBIC . pKLIC . plogLik . plot.mcglm . print.mcglm . residuals.mcglm . soil . soya . summary.mcglm . vcov.mcglm .
Some associated R codes: RcppExports.R . fit_mcglm.R . mc_KLIC.R . mc_RJC.R . mc_S3_methods.R . mc_anova_disp.R . mc_auxiliar.R . mc_bias_correct_std.R . mc_build_C.R . mc_build_F.R . mc_build_bdiag.R . mc_build_omega.R . mc_build_sigma.R . mc_build_sigmab.R . mc_car.R . mc_complete_data.R . mc_compute_rho.R . mc_conditional_test.R . mc_core_cross_variability.R . mc_core_pearson.R . mc_correction.R . mc_cross_sensitivity.R . mc_cross_variability.R . mc_derivative_C_rho.R . mc_derivative_cholesky.R . mc_derivative_expm.R . mc_derivative_sigma_beta.R . mc_dexp_gold.R . mc_dexpm.R . mc_dglm.R . mc_dist.R . mc_ess.R . mc_getInformation.R . mc_gof.R . mc_gosho.R . mc_id.R . mc_initial_values.R . mc_link_function.R . mc_list2vec.R . mc_ma.R . mc_main_function.R . mc_manova.R . mc_manova_disp.R . mc_matrix_linear_predictor.R . mc_mixed.R . mc_ns.R . mc_pAIC.R . mc_pBIC.R . mc_pearson.R . mc_plogLik.R . mc_quasi_score.R . mc_remove_na.R . mc_robust_std.R . mc_rw.R . mc_sensitivity.R . mc_sic.R . mc_sic_covariance.R . mc_transform_list_bdiag.R . mc_twin.R . mc_updatedBeta.R . mc_updatedCov.R . mc_variability.R . mc_variance_function.R . mcglm.R . zzz_onAttach.R . Full mcglm package functions and examples
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