Package: glmmfields 0.1.8
Sean C. Anderson
glmmfields: Generalized Linear Mixed Models with Robust Random Fields for Spatiotemporal Modeling
Implements Bayesian spatial and spatiotemporal models that optionally allow for extreme spatial deviations through time. 'glmmfields' uses a predictive process approach with random fields implemented through a multivariate-t distribution instead of the usual multivariate normal. Sampling is conducted with 'Stan'. References: Anderson and Ward (2019) <doi:10.1002/ecy.2403>.
Authors:
glmmfields_0.1.8.tar.gz
glmmfields_0.1.8.zip(r-4.5)glmmfields_0.1.8.zip(r-4.4)glmmfields_0.1.8.zip(r-4.3)
glmmfields_0.1.8.tgz(r-4.4-x86_64)glmmfields_0.1.8.tgz(r-4.4-arm64)glmmfields_0.1.8.tgz(r-4.3-x86_64)glmmfields_0.1.8.tgz(r-4.3-arm64)
glmmfields_0.1.8.tar.gz(r-4.5-noble)glmmfields_0.1.8.tar.gz(r-4.4-noble)
glmmfields.pdf |glmmfields.html✨
glmmfields/json (API)
NEWS
| # Install 'glmmfields' in R: |
| install.packages('glmmfields', repos = c('https://noaa-fisheries-integrated-toolbox.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/seananderson/glmmfields/issues
ecologyextremesspatial-analysisspatiotemporal
Last updated 12 months agofrom:ddf3b77ca8. Checks:OK: 1 NOTE: 8. Indexed: no.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Sep 26 2024 |
| R-4.5-win-x86_64 | NOTE | Sep 26 2024 |
| R-4.5-linux-x86_64 | NOTE | Sep 26 2024 |
| R-4.4-win-x86_64 | NOTE | Sep 26 2024 |
| R-4.4-mac-x86_64 | NOTE | Sep 26 2024 |
| R-4.4-mac-aarch64 | NOTE | Sep 26 2024 |
| R-4.3-win-x86_64 | NOTE | Sep 26 2024 |
| R-4.3-mac-x86_64 | NOTE | Sep 26 2024 |
| R-4.3-mac-aarch64 | NOTE | Sep 26 2024 |
Exports:glmmfieldshalf_tlognormalloonbinom2posterior_linpredposterior_predictpredictive_intervalsim_glmmfieldsstudent_ttidy
Dependencies:abindassertthatbackportsBHbroombroom.mixedcallrcheckmatecliclustercodacodetoolscolorspacecpp11descdigestdistributionaldplyrfansifarverforcatsfurrrfuturegenericsggplot2globalsgluegridExtragtableinlineisobandlabelinglatticelifecyclelistenvloomagrittrMASSMatrixmatrixStatsmgcvmunsellmvtnormnlmenumDerivparallellypillarpkgbuildpkgconfigplyrposteriorprocessxpspurrrQuickJSRR6RColorBrewerRcppRcppEigenRcppParallelreshape2rlangrstanrstantoolsscalesStanHeadersstringistringrtensorAtibbletidyrtidyselectutf8vctrsviridisLitewithr
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| The 'glmmfields' package. | glmmfields-package |
| Format data for fitting a glmmfields model | format_data |
| Fit a spatiotemporal random fields GLMM | glmmfields |
| Lognormal family | lognormal |
| Return LOO information criteria | loo loo.glmmfields |
| Negative binomial family | nbinom2 |
| Plot predictions from an glmmfields model | plot.glmmfields |
| Predict from a glmmfields model | posterior_linpred posterior_linpred.glmmfields posterior_predict posterior_predict.glmmfields predict predict.glmmfields predictive_interval predictive_interval.glmmfields |
| Simulate a random field with a MVT distribution | sim_glmmfields |
| Return a vector of parameters | stan_pars |
| Student-t and half-t priors | half_t student_t |
| Tidy model output | tidy tidy.glmmfields |
