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:

2.93 score 1 stars 17 scripts 370 downloads 10 exports 40 dependencies

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

Target	Result	Time
linux-devel-x86_64	NOTE	463
source / vignettes	OK	269
linux-release-x86_64	NOTE	442
macos-release-arm64	NOTE	204
macos-oldrel-arm64	NOTE	269
windows-devel	NOTE	231
windows-release	NOTE	240
windows-oldrel	NOTE	237
wasm-release	OK	142

Exports:algnaive12 derivcormatrix derivQfun distmatrix localinfmeas predgraphics predSCL rspacens SAEMSCL Seminaive

Dependencies:BH cli expm generics geoR glue gmm GPArotation lattice lifecycle magrittr MASS Matrix mnormt moments msm mvtnorm nlme nloptr numDeriv optimx pillar pkgconfig pracma psych raster Rcpp RcppEigen rlang sandwich sp splancs survival terra tibble tlrmvnmvt tmvtnorm utf8 vctrs zoo

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Naive 1 and Naive 2 method for spatial prediction.	algnaive12
Depths of a geological horizon.	depth
First and second derivates of some correlation matrix	derivcormatrix
Maximum Likelihood Expectation (logQ function and its derivates)	derivQfun
Distance matrix	distmatrix
Local influence measures.	localinfmeas
TCDD concentrations in Missouri (1971).	Missouri
Prediction graphics for SAEM Algortihm for censored spatial data.	predgraphics
Prediction for the SAEM algorithm for censored spatial data.	predSCL
Censored Spatial data simulation	rspacens
SAEM Algorithm estimation for censored spatial data.	SAEMSCL
Seminaive algorithm for spatial censored prediction.	Seminaive
Summary of a naive object	summary.naive
Summary of a SAEMSpatialCens object.	summary.SAEMSpatialCens
Summary of a seminaive object	summary.seminaive