Package: jtdm 0.1-3

jtdm: Joint Modelling of Functional Traits

Fitting and analyzing a Joint Trait Distribution Model. The Joint Trait Distribution Model is implemented in the Bayesian framework using conjugate priors and posteriors, thus guaranteeing fast inference. In particular the package computes joint probabilities and multivariate confidence intervals, and enables the investigation of how they depend on the environment through partial response curves. The method implemented by the package is described in Poggiato et al. (2023) <doi:10.1111/geb.13706>.

Authors:Giovanni Poggiato [aut, cre, cph]

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jtdm.pdf |jtdm.html
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NEWS

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

Peer review:

Bug tracker:https://github.com/giopogg/jtdm/issues

Datasets:
  • X - Site x environmental covariates dataset
  • Y - Site x CWM traits dataset

On CRAN:

9 exports 8 stars 1.59 score 43 dependencies 7 scripts 245 downloads

Last updated 9 days agofrom:1c04e3da1d. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 09 2024
R-4.5-winOKSep 09 2024
R-4.5-linuxOKSep 09 2024
R-4.4-winOKSep 09 2024
R-4.4-macOKSep 09 2024
R-4.3-winOKSep 09 2024
R-4.3-macOKSep 09 2024

Exports:ellipse_plotget_sigmagetBjoint_trait_probjoint_trait_prob_gradientjtdm_fitjtdm_predictjtdmCVpartial_response

Dependencies:clicolorspacecpp11fansifarverggforceggplot2gluegridExtragtableisobandlabelinglatticelifecyclemagrittrMASSMatrixmgcvmniwmunsellmvtnormnlmepillarpkgconfigplyrpolyclipR6RColorBrewerRcppRcppEigenreshape2rlangscalesstringistringrsystemfontstibbletidyselecttweenrutf8vctrsviridisLitewithr

ORCHAMP_dataset

Rendered fromORCHAMP_dataset.Rmdusingknitr::rmarkdownon Sep 09 2024.

Last update: 2023-01-23
Started: 2023-01-18