Package: dirinla 1.0.5.9001

Joaquín Martínez-Minaya

dirinla: Hierarchical Bayesian Dirichlet regression models using Integrated Nested Laplace Approximation

The R-package dirinla allows the user to fit models in the compositional data context. In particular, it allows fit Dirichlet regression models using the Integrated Nested Laplace Approximation (INLA) methodology.

Authors:Joaquín Martínez-Minaya [aut, cre], Finn Lindgren [aut]

dirinla_1.0.5.9001.tar.gz
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manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
dirinla/json (API)

# Install 'dirinla' in R:

install.packages('dirinla', repos = c('https://inlabru-org.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/inlabru-org/dirinla/issues

Pkgdown/docs site:https://inlabru-org.github.io

On CRAN:

3.51 score 5 stars 13 scripts 10 exports 50 dependencies

Last updated from:db1b64eab3. Checks:7 NOTE, 2 OK. Indexed: yes.

Target	Result	Time
linux-devel-x86_64	NOTE	208
source / vignettes	OK	242
linux-release-x86_64	NOTE	229
macos-release-arm64	NOTE	162
macos-oldrel-arm64	NOTE	124
windows-devel	NOTE	221
windows-release	NOTE	175
windows-oldrel	NOTE	162
wasm-release	OK	173

Exports:data_stack_dirich data_stack_dirich_formula dirichlet_log_pos_x dirinla_safe_inla dirinlareg dirinlaregmodel extract_fixed extract_linear_predictor formula_list summary_fast

Dependencies:bayesm BH cli compositions cpp11 DEoptimR dplyr farver generics ggplot2 ggtern glue gridExtra gtable hexbin isoband labeling latex2exp lattice lifecycle magrittr MASS Matrix pillar pkgconfig plyr proto purrr R6 RColorBrewer Rcpp RcppArmadillo RcppParallel Rfast Rfast2 rlang Rnanoflann robustbase S7 scales stringi stringr tensorA tibble tidyselect utf8 vctrs viridisLite withr zigg

Articles list

Package examples | Package vignettes

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Last update: 2024-11-15
Started: 2024-11-15

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
dirinla	dirinla-package dirinla
Block diagonal matrix creation	bdiag_m
Preparing the data	data_stack_dirich
Preparing the data	data_stack_dirich_formula
Computing the function digamma	digamma_red
Dirichlet log posterior function	dirichlet_log_pos_x
Fitting a Dirichlet regression	dirinlareg
Defining a new class	dirinlaregmodel
Extracting marginals fixed of an inla object	extract_fixed
Extracting posterior distributions from the linear predictor	extract_linear_predictor
Formula in to list	formula_list
Computing gradient vector in eta	g0_vector_eta_1
Computing additional diagonal part for the real Hessian H = H0 + diag	H_matrix_eta_diag
Computing expected Hessian in eta	H0_matrix_eta_x
Computing expected Hessian for a vector eta	H0_matrix_eta1
Calculating the log beta function in eta	log_beta_mult_eta
Finding the mode of the full posterior distribution	look_for_mode_x
Newton-Raphson algorithm	newton_x
plot of dirinlaregmodel xs	plot.dirinlaregmodel
Finding the mode of the full posterior distribution	predict.dirinlaregmodel
Summary using the packages Rfast and Rfast2 of a matrix by rows	summary_fast
Summary of dirinlaregmodel objects	summary.dirinlaregmodel
Computing the function trigamma	trigamma_red