Crandore Hub

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.

Versions across snapshots

VersionRepositoryFileSize
0.1.0 rolling linux/jammy R-4.5 SumcaVer1_0.1.0.tar.gz 176.7 KiB
0.1.0 rolling linux/noble R-4.5 SumcaVer1_0.1.0.tar.gz 176.6 KiB
0.1.0 rolling source/ R- SumcaVer1_0.1.0.tar.gz 42.5 KiB
0.1.0 latest linux/jammy R-4.5 SumcaVer1_0.1.0.tar.gz 176.7 KiB
0.1.0 latest linux/noble R-4.5 SumcaVer1_0.1.0.tar.gz 176.6 KiB
0.1.0 latest source/ R- SumcaVer1_0.1.0.tar.gz 42.5 KiB
0.1.0 2026-04-26 source/ R- SumcaVer1_0.1.0.tar.gz 42.5 KiB
0.1.0 2026-04-23 source/ R- SumcaVer1_0.1.0.tar.gz 42.5 KiB
0.1.0 2026-04-09 windows/windows R-4.5 SumcaVer1_0.1.0.zip 174.4 KiB
0.1.0 2025-04-20 source/ R- SumcaVer1_0.1.0.tar.gz 42.5 KiB

Dependencies (latest)

Imports