Package: nimblewomble 0.1.0

nimblewomble: Bayesian Wombling using Nimble

Performs Bayesian Wombling using Nimble. For more details on wombling please see, <doi:10.1198/016214506000000041> and <doi:10.1080/01621459.2023.2177166>.

Authors:Aritra Halder [aut, cre], Sudipto Banerjee [aut]

nimblewomble_0.1.0.tar.gz
nimblewomble_0.1.0.zip(r-4.7)nimblewomble_0.1.0.zip(r-4.6)nimblewomble_0.1.0.zip(r-4.5)
nimblewomble_0.1.0.tgz(r-4.6-any)nimblewomble_0.1.0.tgz(r-4.5-any)
nimblewomble_0.1.0.tar.gz(r-4.7-any)nimblewomble_0.1.0.tar.gz(r-4.6-any)
nimblewomble_0.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
nimblewomble/json (API)

# Install 'nimblewomble' in R:
install.packages('nimblewomble', repos = c('https://arh926.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/arh926/nimblewomble/issues

On CRAN:

Conda:

bayesiannimblewombling

2.70 score 1 stars 181 downloads 24 exports 76 dependencies

Last updated from:1292bafa0e. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK248
source / vignettesOK198
linux-release-x86_64OK244
macos-release-arm64OK240
macos-oldrel-arm64OK246
windows-develOK233
windows-releaseOK201
windows-oldrelOK203
wasm-releaseOK149

Exports:curvatures_gaussiancurvatures_matern2gamma_intgamma1.mcov1gamma1n2.gaussgamma1n2.mcov2gaussiangp_fitgradients_matern1materncov1materncov2pnorm_nimblesignificancesp_ggplotspratesspwomblingwombling_gaussianwombling_matern1wombling_matern2zbeta_gaussianzbeta_matern1zbeta_matern2zbeta_sampleszXbeta

Dependencies:abindbackportsBHcachemcheckmateclassclassIntclicodacpp11crayoncurldata.tableDBIdigestdplyre1071farverfastmapFormulaformula.toolsgenericsggplot2ggspatialgluegtablehmsigraphisobandjpegKernSmoothlabelinglatticelifecyclelubridatemagrittrMASSMatrixMBAmemoisemetRnimblenumDerivoperator.toolspillarpkgconfigplyrpngpracmaprettyunitsprogressproxypurrrR6RColorBrewerRcpprlangrosms2S7scalessfspstringistringrterratibbletidyrtidyselecttimechangeunitsutf8vctrsviridisLitewithrwk

Readme and manuals

Help Manual

Help pageTopics
Posterior samples of rates of change (gradients and curvatures) for the Matern kernel with nu\toInf producing the squared exponential kernel.curvatures_gaussian
Posterior samples of rates of change (gradients and curvatures) for the Matern kernel with nu=5/2curvatures_matern2
Incomplete Gamma Functiongamma_int
Cross-covariance terms for the posterior distribution of wombling measures for Matern nu=3/2.gamma1.mcov1
Cross-covariance terms for the posterior distribution of wombling measures for Matern nu\toInf, the squared exponential kernel.gamma1n2.gauss
Cross-covariance terms for the posterior distribution of wombling measures for Matern nu=5/2, the squared exponential kernel.gamma1n2.mcov2
Squared Exponential Covariance kernelgaussian
Fit a Gaussian processgp_fit
Posterior samples of rates of change (gradients) for the Matern kernel with nu=3/2gradients_matern1
Matern Covariance kernel with nu = 3/2materncov1
Matern Covariance kernel with nu = 5/2materncov2
Computes the Cumulative Distribution Function for the standard Gaussian probability distributionpnorm_nimble
Determines significance for posterior estimatessignificance
Spatial Plot Functionsp_ggplot
Posterior samples for rates of changesprates
Posterior samples for wombling measuresspwombling
Posterior samples for wombling measures for the squared exponential kernelwombling_gaussian
Posterior samples for wombling measures from the Matern kernel with nu=3/2wombling_matern1
Posterior samples for wombling measures from the Matern kernel with nu=5/2wombling_matern2
Posterior samples of spatial effects and intercept for the squared exponential kernelzbeta_gaussian
Posterior samples of spatial effects and intercept for the Matern kernel with nu=3/2zbeta_matern1
Posterior samples of spatial effects and intercept for the Matern kernel with nu=5/2zbeta_matern2
Posterior samples of spatial effects and intercept for Matern with nu=3/2zbeta_samples
Posterior samples of spatial effects and intercept for all kernels in the presence of covariateszXbeta