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RcppCensSpatial
View on CRAN: Click
here
Download and install RcppCensSpatial package within the R console
Install from CRAN:
install.packages("RcppCensSpatial")
Install from Github:
library("remotes")
install_github("cran/RcppCensSpatial")
Install by package version:
library("remotes")
install_version("RcppCensSpatial", "0.3.0")
Attach the package and use:
library("RcppCensSpatial")
Maintained by
Katherine A. L. Valeriano
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2021-09-21
Latest Update: 2022-06-27
Description:
It provides functions to estimate parameters in linear spatial models with censored/missing responses via the Expectation-Maximization (EM), the Stochastic Approximation EM (SAEM), or the Monte Carlo EM (MCEM) algorithm. These algorithms are widely used to compute the maximum likelihood (ML) estimates in problems with incomplete data. The EM algorithm computes the ML estimates when a closed expression for the conditional expectation of the complete-data log-likelihood function is available. In the MCEM algorithm, the conditional expectation is substituted by a Monte Carlo approximation based on many independent simulations of the missing data. In contrast, the SAEM algorithm splits the E-step into simulation and integration steps. This package also approximates the standard error of the estimates using the Louis method. Moreover, it has a function that performs spatial prediction in new locations.
How to cite:
Katherine A. L. Valeriano (2021). RcppCensSpatial: Spatial Estimation and Prediction for Censored/Missing Responses. R package version 0.3.0, https://cran.r-project.org/web/packages/RcppCensSpatial
Previous versions and publish date:
0.1.0 (2021-09-21 15:50)
Other packages that cited RcppCensSpatial R package
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Other R packages that RcppCensSpatial depends,
imports, suggests or enhances
Functions, R codes and Examples using
the RcppCensSpatial R package
Some associated functions: CovMat . EM.sclm . MCEM.sclm . Missouri . SAEM.sclm . dist2Dmatrix . predict.sclm . rCensSp .
Some associated R codes: Algorithm_utils.R . AuxiliaryFunctions_USER.R . EstEMspatial_USER.R . EstMCEMspatial_USER.R . EstSAEMspatial_USER.R . RcppCensSpatial-package.R . RcppExports.R . data.R . rCensspatial_USER.R . Full RcppCensSpatial package functions and examples
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