This package is considered a duplicate. The official version of this package is found at:https://exce1sior1008.r-universe.dev/saeMSPE

Package: saeMSPE 1.4

Peiwen Xiao

saeMSPE: Computing MSPE Estimates in Small Area Estimation

Compute various common mean squared predictive error (MSPE) estimators, as well as several existing variance component predictors as a byproduct, for FH model (Fay and Herriot, 1979) and NER model (Battese et al., 1988) in small area estimation.

Authors:Peiwen Xiao [aut, cre], Xiaohui Liu [aut], Yu Zhang [aut], Yuzi Liu [aut], Jiming Jiang [ths]

saeMSPE_1.4.tar.gz
saeMSPE_1.4.zip(r-4.7)saeMSPE_1.4.zip(r-4.6)saeMSPE_1.4.zip(r-4.5)
saeMSPE_1.4.tgz(r-4.6-x86_64)saeMSPE_1.4.tgz(r-4.6-arm64)saeMSPE_1.4.tgz(r-4.5-x86_64)saeMSPE_1.4.tgz(r-4.5-arm64)
saeMSPE_1.4.tar.gz(r-4.7-arm64)saeMSPE_1.4.tar.gz(r-4.7-x86_64)saeMSPE_1.4.tar.gz(r-4.6-arm64)saeMSPE_1.4.tar.gz(r-4.6-x86_64)
saeMSPE_1.4.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
saeMSPE/json (API)

# Install 'saeMSPE' in R:

install.packages('saeMSPE', repos = c('https://cranhaven.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/cranhaven/cranhaven.r-universe.dev/issues

Uses libs:

openblas– Optimized BLAS
c++– GNU Standard C++ Library v3
openmp– GCC OpenMP (GOMP) support library

Datasets:

wheatarea - Wheat area measurement and satellite data.

On CRAN:

archived packages r-universe openblas cpp openmp

1.78 score 5 stars 12 scripts 215 downloads 19 exports 6 dependencies

Last updated from:092b130857 (on package/saeMSPE). Checks:13 OK. Indexed: no.

Target	Result	Time
linux-devel-arm64	OK	140
linux-devel-x86_64	OK	145
source / vignettes	OK	183
linux-release-arm64	OK	174
linux-release-x86_64	OK	132
macos-release-arm64	OK	98
macos-release-x86_64	OK	250
macos-oldrel-arm64	OK	124
macos-oldrel-x86_64	OK	322
windows-devel	OK	158
windows-release	OK	139
windows-oldrel	OK	132
wasm-release	OK	141

Exports:mspeFHdb mspeFHDL mspeFHDRS mspeFHjack mspeFHlin mspeFHMPR mspeFHpb mspeFHPR mspeFHsumca mspeNERdb mspeNERDL mspeNERjack mspeNERlin mspeNERpb mspeNERPR mspeNERsumca varfh varner varOBP

Dependencies:lattice MASS Matrix Rcpp RcppArmadillo smallarea

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Compute MSPE Estimates for the Fay Herriot Model and Nested Error Regression Model	saeMSPE-package saeMSPE
Compute MSPE through double bootstrap method for Fay Herriot model	mspeFHdb
Compute MSPE through Jackknife-based MSPE estimation method for Fay Herriot model	mspeFHjack
Compute MSPE through linearization method for Fay Herriot model	mspeFHDL mspeFHDRS mspeFHlin mspeFHMPR mspeFHPR
Compute MSPE through parameter bootstrap method for Fay Herriot model	mspeFHpb
Compute MSPE through Sumca method for Fay Herriot model	mspeFHsumca
Compute MSPE through double bootstrap(DB) method for Nested error regression model	mspeNERdb
Compute MSPE through Jackknife-based MSPE estimation method for Nested error regression model	mspeNERjack
Compute MSPE through linearization method for Nested error regression model	mspeNERDL mspeNERlin mspeNERPR
Compute MSPE through parameter bootstrap method for Nested error regression model	mspeNERpb
Compute MSPE through Sumca method for Nested error regression model	mspeNERsumca
Estimates of the variance component using several methods for Fay Herriot model	varfh varOBP
Estimates of the variance component using several methods for Nested error regression model.	varner
Wheat area measurement and satellite data.	wheatarea