{ "_id": "6a38eb553efcd9bda443c281", "Package": "BayesSampling", "Type": "Package", "Title": "Bayes Linear Estimators for Finite Population", "Version": "1.1.0", "Date": "2021-04-24", "Authors@R": "c(person(\"Pedro\", \"Soares Figueiredo\", \nrole = c(\"aut\", \"cre\"),\nemail = \"pedrosfig@hotmail.com\",\ncomment = c(ORCID = \"0000-0003-2279-2881\")),\nperson(\"Kelly C.\", \"M. Gonçalves\",\nrole = c(\"aut\", \"ths\"),\nemail = \"kelly@dme.ufrj.br\",\ncomment = c(ORCID = \"0000-0002-4524-547X\")))", "Maintainer": "Pedro Soares Figueiredo ", "Description": "Allows the user to apply the Bayes Linear approach to\nfinite population with the Simple Random Sampling - BLE_SRS() -\nand the Stratified Simple Random Sampling design - BLE_SSRS() -\n(both without replacement), to the Ratio estimator (using\nauxiliary information) - BLE_Ratio() - and to categorical data\n- BLE_Categorical(). The Bayes linear estimation approach is\napplied to a general linear regression model for finite\npopulation prediction in BLE_Reg() and it is also possible to\nachieve the design based estimators using vague prior\ndistributions. Based on Gonçalves, K.C.M, Moura, F.A.S and\nMigon, H.S.(2014)\n.", "URL": "https://www150.statcan.gc.ca/n1/en/catalogue/12-001-X201400111886,\nhttps://github.com/pedrosfig/BayesSampling", "License": "GPL-3", "Encoding": "UTF-8", "LazyData": "true", "RoxygenNote": "7.1.1", "VignetteBuilder": "knitr", "Language": "en-US", "Repository": "https://pedrosfig.r-universe.dev", "Date/Publication": "2021-05-01 18:20:39 UTC", "RemoteUrl": "https://github.com/pedrosfig/bayessampling", "RemoteRef": "HEAD", "RemoteSha": "13095496b1d1c2c51167e3e7d59446a4319aae0e", "NeedsCompilation": "no", "Packaged": { "Date": "2026-06-22 07:56:00 UTC", "User": "root" }, "Author": "Pedro Soares Figueiredo [aut, cre] (ORCID:\n),\nKelly C. M. 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