Package: SumcaVer1 0.1.0

SumcaVer1: Mean Square Prediction Error Estimation in Small Area Estimation

Estimation of mean squared prediction error of a small area predictor is provided. In particular, the recent method of Simple, Unified, Monte-Carlo Assisted approach for the mean squared prediction error estimation of small area predictor is provided. We also provide other existing methods of mean squared prediction error estimation such as jackknife method for the mixed logistic model.

Authors:Mahmoud Torabi [aut, cre], Jiming Jiang [ctb]

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SumcaVer1.pdf |SumcaVer1.html✨
SumcaVer1/json (API)

# Install 'SumcaVer1' in R:
install.packages('SumcaVer1', repos = c('https://torabi-uofm.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.00 score 119 downloads 12 exports 13 dependencies

Last updated 4 months agofrom:2220376ad1. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 29 2024
R-4.5-winOKOct 29 2024
R-4.5-linuxOKOct 29 2024
R-4.4-winOKOct 29 2024
R-4.4-macOKOct 29 2024
R-4.3-winOKOct 29 2024
R-4.3-macOKOct 29 2024

Exports:mspe_FH_Bootmspe_FH_PRmspe_FH_Sumcamspe_LOGISTIC_HealthData_BOOTmspe_LOGISTIC_HealthData_JLWmspe_LOGISTIC_HealthData_SUMCAmspe_MS_LOGISTIC_JLWmspe_MS_LOGISTIC_SUMCAmspe_PMS_FH_DHMmspe_PMS_FH_SUMCAmspe_PMS_Mis_FH_DHMmspe_PMS_Mis_FH_SUMCA

Dependencies:bootGPArotationlatticelme4MASSMatrixminqamnormtnlmenloptrpsychRcppRcppEigen

Readme and manuals

Help Manual

Help pageTopics
MSPE estimation in FH model using double-phase bootstrap method.Calculate the mspe of Fay-Herriot model in SAE using double-phase bootstrap method.mspe_FH_Boot
MSPE estimation in FH model using Prasad-Rao method. Calculate the mspe of Fay-Herriot model in SAE using Prasad-Rao method.mspe_FH_PR
MSPE estimation in FH model using SUMCA method. Calculate the mspe of Fay-Herriot model in SAE using Sumca method.mspe_FH_Sumca
MSPE estimation in mixed logistic model (Health Insurance data) using bootstrap method. Calculate the mspe of mixed logistic model (Health Insurance data) using bootstrap method.mspe_LOGISTIC_HealthData_BOOT
MSPE estimation in mixed logistic model (Health Insurance data) using jackknife method.Calculate the mspe of mixed logistic model (Health Insurance data) using jackknife method.mspe_LOGISTIC_HealthData_JLW
MSPE estimation in mixed logistic model (Health Insurance data) using SUMCA method.Calculate the mspe of mixed logistic model (Health Insurance data) using SUMCA method.mspe_LOGISTIC_HealthData_SUMCA
Model selection MSPE estimation in mixed logistic model using jackknife method.Calculate the model selection mspe of mixed logistic model using jackknife method.mspe_MS_LOGISTIC_JLW
Model selection MSPE estimation in mixed logistic model using SUMCA method. Calculate the model selection mspe of mixed logistic model using SUMCA method.mspe_MS_LOGISTIC_SUMCA
Post model selection MSPE estimation in FH model using Datta-Hall-Mandal method. Calculate the post-model selection mspe of Fay-Herriot model using Datta-Hall-Mandal method.mspe_PMS_FH_DHM
Post model selection MSPE estimation in FH model using SUMCA method. Calculate the post-model selection mspe of Fay-Herriot model using SUMCA method.mspe_PMS_FH_SUMCA
Post model selection MSPE estimation in FH model with mean mis-specification using Datta-Hall-Mandal method. Calculate the post-model selection mspe of Fay-Herriot model with mean mis-specification using Datta-Hall-Mandal method.mspe_PMS_Mis_FH_DHM
Post model selection MSPE estimation in FH model with mean mis-specification using SUMCA method. Calculate the post-model selection mspe of Fay-Herriot model with mean mis-specification using SUMCA method.mspe_PMS_Mis_FH_SUMCA