Package: MRFcov 1.0.39

MRFcov: Markov Random Fields with Additional Covariates

Approximate node interaction parameters of Markov Random Fields graphical networks. Models can incorporate additional covariates, allowing users to estimate how interactions between nodes in the graph are predicted to change across covariate gradients. The general methods implemented in this package are described in Clark et al. (2018) <doi:10.1002/ecy.2221>.

Authors:Nicholas J Clark [aut, cre], Konstans Wells [aut], Oscar Lindberg [aut]

MRFcov_1.0.39.tar.gz
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MRFcov_1.0.39.tgz(r-4.6-any)MRFcov_1.0.39.tgz(r-4.5-any)
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MRFcov_1.0.39.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
MRFcov/json (API)

# Install 'MRFcov' in R:
install.packages('MRFcov', repos = c('https://nicholasjclark.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/nicholasjclark/mrfcov/issues

Datasets:

On CRAN:

Conda:

conditional-random-fieldsgraphical-modelsmachine-learningmarkov-random-fieldmultivariate-analysismultivariate-statisticsnetwork-analysisnetworks

6.09 score 25 stars 33 scripts 384 downloads 11 exports 80 dependencies

Last updated from:91d77124c0. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK213
source / vignettesOK253
linux-release-x86_64OK177
macos-release-arm64OK142
macos-oldrel-arm64OK151
windows-develOK101
windows-releaseOK124
windows-oldrelOK130
wasm-releaseOK161

Exports:bootstrap_MRFcv_MRF_diagcv_MRF_diag_repcv_MRF_diag_rep_spatialMRFcovMRFcov_spatialplotMRF_hmpredict_MRFpredict_MRFnetworksprep_MRF_covariatesprep_MRF_covariates_spatial

Dependencies:caretclasscliclockcodetoolscpp11data.tablediagramdigestdplyre1071farverforeachfuturefuture.applygenericsggplot2glmnetglobalsgluegowergridExtragtablehardhatigraphipredisobanditeratorsKernSmoothlabelinglatticelavalifecyclelistenvlubridatemagrittrMASSMatrixmgcvModelMetricsnlmennetnumDerivparallellypbapplypillarpkgconfigplyrpROCprodlimprogressrproxypurrrR6RColorBrewerRcppRcppEigenrecipesreshape2rlangrpartS7scalessfsmiscshapesparsevctrsSQUAREMstringistringrsurvivaltibbletidyrtidyselecttimechangetimeDatetzdbutf8vctrsviridisLitewithr

MRFs and CRFs for Bird.parasites data
<<<<<<< HEAD | title: "MRFs and CRFs for Bird.parasites data"output: rmarkdown::html_vignettevignette: >%\VignetteIndexEntry | Running MRFs and visualising interaction coefficients | Running CRFs using additional covariates | Comparing fits of MRF and CRF models | Bootstrapping the data and running models | Exploring regression coefficients and interpreting results | Accounting for possible spatial autocorrelation | =======
Rendered fromBird_Parasite_CRF.Rmdusingknitr::rmarkdown

Last update: 2023-04-04
Started: 2018-03-04

Gaussian and Poisson CRFs
Rendered fromGaussian_Poisson_CRFs.Rmdusingknitr::rmarkdown

Last update: 2023-01-12
Started: 2018-08-27

Prepping datasets for CRF models
Running CRFs with categorical covariates requires expansion to model matrix format
Rendered fromCRF_data_prep.Rmdusingknitr::rmarkdown

Last update: 2023-01-12
Started: 2018-03-04