Package: glmSTARMA 1.0.0

Steffen Maletz

glmSTARMA: (Double) Generalized Linear Models for Spatio-Temporal Data

Fit spatio-temporal models within a (double) generalized linear modelling framework. The package includes functions for estimation, simulation and inference.

Authors:Steffen Maletz [aut, cre], Konstantinos Fokianos [aut], Roland Fried [aut], Valerie Weismann [ctb]

glmSTARMA_1.0.0.tar.gz
glmSTARMA_1.0.0.zip(r-4.7)glmSTARMA_1.0.0.zip(r-4.6)glmSTARMA_1.0.0.zip(r-4.5)
glmSTARMA_1.0.0.tgz(r-4.6-x86_64)glmSTARMA_1.0.0.tgz(r-4.6-arm64)glmSTARMA_1.0.0.tgz(r-4.5-x86_64)glmSTARMA_1.0.0.tgz(r-4.5-arm64)
glmSTARMA_1.0.0.tar.gz(r-4.7-arm64)glmSTARMA_1.0.0.tar.gz(r-4.7-x86_64)glmSTARMA_1.0.0.tar.gz(r-4.6-arm64)glmSTARMA_1.0.0.tar.gz(r-4.6-x86_64)
glmSTARMA_1.0.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
glmSTARMA/json (API)

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

Bug tracker:https://github.com/stmaletz/glmstarma/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3

On CRAN:

Conda:

openblascpp

3.30 score 1 scripts 143 downloads 21 exports 16 dependencies

Last updated from:ad5da2f27c. Checks:13 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK231
linux-devel-x86_64OK216
source / vignettesOK275
linux-release-arm64OK233
linux-release-x86_64OK212
macos-release-arm64OK162
macos-release-x86_64OK279
macos-oldrel-arm64OK217
macos-oldrel-x86_64OK306
windows-develOK241
windows-releaseOK224
windows-oldrelOK241
wasm-releaseOK175

Exports:delete_glmSTARMA_datadglmstarmadglmstarma.controldglmstarma.simgenerateWglmstarmaglmstarma_sim.controlglmstarma.controlglmstarma.simload_dataQICSpatialConstantTimeConstantvbinomialvgammavinverse.gaussianvnegative.binomialvnormalvpoissonvquasibinomialvquasipoisson

Dependencies:ADGofTestclustercolorspacecopulagsllatticeMatrixmvtnormnloptrnumDerivpcaPPpsplineRcppRcppArmadilloroptimstabledist

Readme and manuals

Help Manual

Help pageTopics
glmSTARMA: (Double) Generalized Linear Models for Spatio-Temporal DataglmSTARMA-package glmSTARMA
Chickenpox Infections in Hungarychickenpox
Extract Coefficients of glmstarma and dglmstarma Modelscoef.dglmstarma coef.glmstarma
Delete cached example datasetsdelete_glmSTARMA_data
Fit STARMA Models based on double generalized linear modelsdglmstarma
Control Parameters for 'dglmstarma' Fittingdglmstarma.control
Simulate spatial time-series based on double generalized linear modelsdglmstarma.sim
Fitted values for glmstarma Modelsfitted.dglmstarma fitted.glmstarma
Generate spatial weight matrices for simulationgenerateW
Fit STARMA Models based on generalized linear modelsglmstarma
Control Parameters for Simulation of 'glmstarma' Modelsglmstarma_sim.control
Control Parameters for 'glmstarma' Fittingglmstarma.control
Simulate spatial time-series based on generalized linear modelsglmstarma.sim
Information Criteria for glmstarma and dglmstarma objectsAIC.dglmstarma AIC.glmstarma BIC.dglmstarma BIC.glmstarma information_criteria logLik.dglmstarma logLik.glmstarma
Load example datasetsload_data
Quasi Information Criterion (QIC) for glmstarma and dglmstarma objectsQIC QIC.dglmstarma QIC.glmstarma
Residuals for glmstarma and dglmstarma Modelsresiduals.dglmstarma residuals.glmstarma
Rota Virus Infections in Germanyrota
Creates a spatial constant covariateSpatialConstant
Sea Surface Temperature Anomalies in the Pacificsst
Families for spatio-temporal GLMsstfamily vbinomial vgamma vinverse.gaussian vnegative.binomial vnormal vpoisson vquasibinomial vquasipoisson
Summarize a dglmstarma Modelsummary.dglmstarma
Summarize the results of a glmstarma modelsummary.glmstarma
Creates a time constant covariateTimeConstant
Variance-Covariance Matrix for glmstarma and dglmstarma objectssandwich_variance vcov.dglmstarma vcov.glmstarma