Package: CensSpatial 3.6

CensSpatial: Censored Spatial Models

It fits linear regression models for censored spatial data. It provides different estimation methods as the SAEM (Stochastic Approximation of Expectation Maximization) algorithm and seminaive that uses Kriging prediction to estimate the response at censored locations and predict new values at unknown locations. It also offers graphical tools for assessing the fitted model. More details can be found in Ordonez et al. (2018) <doi:10.1016/j.spasta.2017.12.001>.

Authors:Alejandro Ordonez, Christian E. Galarza, Victor H. Lachos

CensSpatial_3.6.tar.gz
CensSpatial_3.6.zip(r-4.7-any)CensSpatial_3.6.zip(r-4.6-any)CensSpatial_3.6.zip(r-4.5-any)
CensSpatial_3.6.tgz(r-4.6-any)CensSpatial_3.6.tgz(r-4.5-any)
CensSpatial_3.6.tar.gz(r-4.7-any)CensSpatial_3.6.tar.gz(r-4.6-any)
CensSpatial_3.6.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
CensSpatial/json (API)

# Install 'CensSpatial' in R:
install.packages('CensSpatial', repos = c('https://joalor93.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/joalor93/censspatial/issues

Datasets:
  • depth - Depths of a geological horizon.
  • Missouri - TCDD concentrations in Missouri (1971).

On CRAN:

Conda:

2.93 score 1 stars 17 scripts 401 downloads 10 exports 40 dependencies

Last updated from:eda79c90e9. Checks:7 NOTE, 2 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develNOTE390
source / vignettesOK218
linux-releaseNOTE403
macos-releaseNOTE352
macos-oldrelNOTE325
windows-develNOTE255
windows-releaseNOTE199
windows-oldrelNOTE157
wasm-releaseOK121

Exports:algnaive12derivcormatrixderivQfundistmatrixlocalinfmeaspredgraphicspredSCLrspacensSAEMSCLSeminaive

Dependencies:BHcliexpmgenericsgeoRgluegmmGPArotationlatticelifecyclemagrittrMASSMatrixmnormtmomentsmsmmvtnormnlmenloptrnumDerivoptimxpillarpkgconfigpracmapsychrasterRcppRcppEigenrlangsandwichspsplancssurvivalterratibbletlrmvnmvttmvtnormutf8vctrszoo