Package: TraitEnvMLMWA 0.9001

TraitEnvMLMWA: Weighted Averaging (WA) and Multi-Level Methods (MLM) for Trait-Environment Association in Functional and Community Ecology

This package grew out of the paper New robust weighted averaging- and model-based methods for assessing trait-environment relationships (Methods in Ecology and Evolution). The model-based methods are GLMMs, here called multi-level models (MLM), of which the novel MLM3 outperforms all existing methods. MLM3 has up to 30% more power, but the WA-methods are 500 times faster than MLM3. The main function for WA-methods is CWMSNC_regressions. The main functions for MLM3 are make_obj_for_traitenv, expand4glmm and MLM3_p_max.

Authors:Cajo ter Braak [aut, cre]

TraitEnvMLMWA_0.9001.tar.gz
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TraitEnvMLMWA_0.9001.tgz(r-4.4-any)TraitEnvMLMWA_0.9001.tgz(r-4.3-any)
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TraitEnvMLMWA.pdf |TraitEnvMLMWA.html
TraitEnvMLMWA/json (API)

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

Peer review:

Bug tracker:https://github.com/cajoterbraak/traitenvmlmwa/issues

Datasets:
  • MLM3 - MLM3-fit to Revisit data using trait C:N ratio and environmental variable TMG
  • MLM3_Aravo - Quadratic MLM3-fit to Aravo data using SLA and Snow
  • Revisit - Revisit data

On CRAN:

1.70 score 8 exports 44 dependencies

Last updated 2 years agofrom:02216b3097. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 17 2024
R-4.5-winOKNov 17 2024
R-4.5-linuxOKNov 17 2024
R-4.4-winOKNov 17 2024
R-4.4-macOKNov 17 2024
R-4.3-winOKNov 17 2024
R-4.3-macOKNov 17 2024

Exports:Bootstrap_test_prmtrcCWMSNC_regressionsdat4MLM2TE_objexpand4glmmmake_obj_for_traitenvMLM3_p_maxplot_MLM3WA_p_max

Dependencies:bootclicolorspacedplyrfansifarvergenericsggplot2glmmTMBgluegtableisobandlabelinglatticelifecyclelme4magrittrMASSMatrixmgcvminqamunsellnlmenloptrnumDerivpermutepillarpkgconfigR6rbibutilsRColorBrewerRcppRcppEigenRdpackreformulasrlangscalestibbletidyselectTMButf8vctrsviridisLitewithr