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CensSpatial

3.6Package record

Censored Spatial Models

0packages depend
3.5Kdownloads / year
–test coverage
9/13flavors OK

Overview

About

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.

Install

Health

CRAN checks
2ERROR2NOTE9OK
Check messages
ERRORexamplesr-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc

r-devel-linux-x86_64-fedora-clang

Running examples in ‘CensSpatial-Ex.R’ failed
The error most likely occurred in:

> ### Name: algnaive12
> ### Title: Naive 1 and Naive 2 method for spatial prediction.
> ### Aliases: algnaive12
> ### Keywords: Spatial Censored SAEM
> 
> ### ** Examples
> 
> ###simulated coordinates
> n<-200 ### sample size for estimation.
> n1=100 ### number of observation used in the prediction.
> 
> ###simulated coordinates
> r1=sample(seq(1,30,length=400),n+n1)
> r2=sample(seq(1,30,length=400),n+n1)
> coords=cbind(r1,r2)### total coordinates (used in estimation and prediction).
> 
> coords1=coords[1:n,]####coordinates used for estimation.
> 
> type="matern"### covariance structure.
> 
> xtot<-cbind(1,runif((n+n1)),runif((n+n1),2,3))## X matrix for estimation and prediction.
> xobs=xtot[1:n,]## X matrix for estimation.
> 
> ###simulated data
> obj=rspacens(cov.pars=c(3,.3,0),beta=c(5,3,1),x=xtot,coords=coords,kappa=1.2,
+ cens=0.25,n=(n+n1),n1=n1,cov.model=type,cens.type="left")
> 
> data2=obj$datare
> data2[,4:5]=xobs[,-1]
> 
> cc=obj$cc
> y=obj$datare[,3]
> cutoff=rep(obj$cutoff,length(y[cc==1]))
> 
> 
> aux2=algnaive12(data=data2,cc=obj$cc,covar=TRUE,covar.col=4:5,
+ copred=obj$coords1,thetaini=c(.1,.2),y.col=3,coords.col=1:2,
+ fix.nugget=TRUE,nugget=0,kappa=1.2,cutoff=cutoff,trend=~V4+V5,
+ cov.model=type)
OMP: Warning #96: Cannot form a team with 28 threads, using 2 instead.
OMP: Hint Consider unsetting KMP_DEVICE_THREAD_LIMIT (KMP_ALL_THREADS), KMP_TEAMS_THREAD_LIMIT, and OMP_THREAD_LIMIT (if any are set).

r-devel-linux-x86_64-fedora-gcc

Running examples in ‘CensSpatial-Ex.R’ failed
The error most likely occurred in:

> ### Name: algnaive12
> ### Title: Naive 1 and Naive 2 method for spatial prediction.
> ### Aliases: algnaive12
> ### Keywords: Spatial Censored SAEM
> 
> ### ** Examples
> 
> ###simulated coordinates
> n<-200 ### sample size for estimation.
> n1=100 ### number of observation used in the prediction.
> 
> ###simulated coordinates
> r1=sample(seq(1,30,length=400),n+n1)
> r2=sample(seq(1,30,length=400),n+n1)
> coords=cbind(r1,r2)### total coordinates (used in estimation and prediction).
> 
> coords1=coords[1:n,]####coordinates used for estimation.
> 
> type="matern"### covariance structure.
> 
> xtot<-cbind(1,runif((n+n1)),runif((n+n1),2,3))## X matrix for estimation and prediction.
> xobs=xtot[1:n,]## X matrix for estimation.
> 
> ###simulated data
> obj=rspacens(cov.pars=c(3,.3,0),beta=c(5,3,1),x=xtot,coords=coords,kappa=1.2,
+ cens=0.25,n=(n+n1),n1=n1,cov.model=type,cens.type="left")
> 
> data2=obj$datare
> data2[,4:5]=xobs[,-1]
> 
> cc=obj$cc
> y=obj$datare[,3]
> cutoff=rep(obj$cutoff,length(y[cc==1]))
> 
> 
> aux2=algnaive12(data=data2,cc=obj$cc,covar=TRUE,covar.col=4:5,
+ copred=obj$coords1,thetaini=c(.1,.2),y.col=3,coords.col=1:2,
+ fix.nugget=TRUE,nugget=0,kappa=1.2,cutoff=cutoff,trend=~V4+V5,
+ cov.model=type)
NOTECRAN incoming feasibilityr-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc
Maintainer: ‘Alejandro Ordonez <ordonezjosealejandro@gmail.com>’

No Authors@R field in DESCRIPTION.
Please add one, modifying
  Authors@R: c(person(given = "Alejandro",
                      family = "Ordonez",
                      role = c("aut", "cre"),
                      email = "ordonezjosealejandro@gmail.com"),
               person(given = c("Christian", "E."),
                      family = "Galarza",
                      role = "aut"),
               person(given = c("Victor", "H."),
                      family = "Lachos",
                      role = "aut"))
as necessary.
NOTEdependencies in R coder-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc
Namespace in Imports field not imported from:
  ‘Rcpp’
All declared Imports should be used.

CRAN check page ↗

Slowest check: 7.8 min · r-patched-linux-x86_64
Status changes
  • ERROR9 OK, 2 NOTE, 2 ERRORNow
  • ERROR10 OK, 2 NOTE, 2 ERROR2026-03-10
Advisories

none known

Documentation

In release 3.6
READMENoVignettesNoNEWSNoCitation fileNoWebsitenot declared in DESCRIPTION
Help pages
15
Examples that run
53%8 run in a plain check · 7 only when donttest examples are enabled (R CMD check --as-cran)
Exported functions with examples
100%
Documented parameters
95%
Return-value docs
100%
Help pages citing references
100%

Downloads

3.5K
CRAN downloads in the past year
Rank #10,423 · ~10/day · ~292/mo
Daily download trend is not available in this view yet.
37230 days
99490 days
3.5K1 year
Compare downloads with other packages →
Also on243 r2u8 autocran

Dependencies

Declared dependencies
11 external dependencies (excludes base and recommended)

Installing CensSpatial adds 35 packages (23 with compiled code, 41 MB of source tarballs). Heaviest: BH 14 MB, sp 4.3 MB, optimx 2.2 MB.

Depends (1)
R >= 4.1.0
LinkingTo (0)
none
Suggests (0)
none
Enhances (0)
none
Reverse dependencies
0direct
0indirect

Nothing depends on this yet.

Datasets

People & History

People (from the free-text Author field) (3)

Maintainer since 1.0 (2016)

Releases (10)

Pick two releases to compare their code metrics.

  • R
    R 4.6.0 released · 2026-04-24
  • R
    R 4.5.0 released · 2025-04-11
  • R
    R 4.4.0 released · 2024-04-24
  • R
    R 4.3.0 released · 2023-04-21
  • 3.6Latest
    record
    2023-01-24 · current release · diff ↗
  • 3.5
    record
    2023-01-17 · diff ↗
  • unarchivedReturned to CRAN
    2022-08-15
  • 3.0
    record
    2022-08-15 · diff ↗
  • archivedRemoved from CRAN
    2022-05-04
    requires archived package 'geoR'
  • R
    R 4.2.0 released · 2022-04-22
  • 2.59
    record
    2021-10-16 · diff ↗
  • R
    R 4.1.0 released · 2021-05-18
  • unarchivedReturned to CRAN
    2020-05-04
  • 2.58
    record
    2020-05-04 · diff ↗
  • R
    R 4.0.0 released · 2020-04-24
  • archivedRemoved from CRAN
    2020-02-03
    check issues were not corrected in time Requires orphaned package 'geoR'
Show 9 earlier eventsHide 9 earlier events
  • 2.1
    record
    2020-01-09 · diff ↗ ·
    removed 1 export
    atypical
  • R
    R 3.6.0 released · 2019-04-26
  • R
    R 3.5.0 released · 2018-04-23
  • R
    R 3.4.0 released · 2017-04-21
  • 1.3
    record
    2017-03-03 · diff ↗
  • 1.2
    record
    2016-12-04 · diff ↗ ·
    added 1 export
    atypical
  • 1.1
    record
    2016-10-17 · diff ↗
  • 1.0
    record
    2016-10-08
  • R
    R 3.3.0 released · 2016-05-03

Package metadata

First published
2016-10-08
Total releases
10 / 10 yrs
License
GPL (>= 2) OSI
Minimum R
≥ 4.1.0
Bundled data
2.4 KB / 2 files
Download size
73 KB

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("CensSpatial")

Cite the R Observatory

For a number measured here: a download total, a coverage figure, an archival date.

APA

Balamuta, J. J. (2026). R Observatory: Metrics for CensSpatial version 3.6 [Data set]. HJJB, LLC. Data release v2026-10-24. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-24, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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