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BayesSampling

Bayes Linear Estimators for Finite Population

Allows the user to apply the Bayes Linear approach to finite population with the Simple Random Sampling - BLE_SRS() - and the Stratified Simple Random Sampling design - BLE_SSRS() - (both without replacement), to the Ratio estimator (using auxiliary information) - BLE_Ratio() - and to categorical data - BLE_Categorical(). The Bayes linear estimation approach is applied to a general linear regression model for finite population prediction in BLE_Reg() and it is also possible to achieve the design based estimators using vague prior distributions. Based on Gonçalves, K.C.M, Moura, F.A.S and Migon, H.S.(2014) <https://www150.statcan.gc.ca/n1/en/catalogue/12-001-X201400111886>.

Versions across snapshots

VersionRepositoryFileSize
1.1.0 rolling linux/jammy R-4.5 BayesSampling_1.1.0.tar.gz 643.7 KiB
1.1.0 rolling linux/noble R-4.5 BayesSampling_1.1.0.tar.gz 643.6 KiB
1.1.0 rolling source/ R- BayesSampling_1.1.0.tar.gz 653.8 KiB
1.1.0 latest linux/jammy R-4.5 BayesSampling_1.1.0.tar.gz 643.7 KiB
1.1.0 latest linux/noble R-4.5 BayesSampling_1.1.0.tar.gz 643.6 KiB
1.1.0 latest source/ R- BayesSampling_1.1.0.tar.gz 653.8 KiB
1.1.0 2026-04-26 source/ R- BayesSampling_1.1.0.tar.gz 653.8 KiB
1.1.0 2026-04-23 source/ R- BayesSampling_1.1.0.tar.gz 653.8 KiB
1.1.0 2026-04-09 windows/windows R-4.5 BayesSampling_1.1.0.zip 667.6 KiB
1.1.0 2025-04-20 source/ R- BayesSampling_1.1.0.tar.gz 653.8 KiB

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