https://mdelapi.r-universe.devRecent package updates in mdelapiR-universehttps://github.com/mdelapi.pnghttps://mdelapi.r-universe.devThu, 01 Oct 2026 04:17:06 GMTphd20x@gmail.com (Miguel Luiz de Almeida Pinto)Planning, selection, and estimation for surveys under the main probability sampling designs taught in introductory sampling courses: simple random sampling with and without replacement, stratified sampling (proportional, Neyman, and cost-based allocation), systematic sampling, one- and two-stage cluster sampling, and ratio and regression estimators. Functions accept a superset of the inputs a given formula requires and silently ignore arguments that are not needed for the selected computation. Each function returns a structured object with the point estimate, the associated variance and confidence interval, a step-by-step breakdown of the calculation, and a short pedagogical note suggesting related methods to explore, making the package suitable both for applied survey work and for classroom use. Methods follow Cochran (1977, ISBN:0-471-16240-X) and Bolfarine & Bussab (2005, ISBN:8521203675), among others referenced in each function's documentation.https://github.com/r-universe/mdelapi/actions/runs/38558628868Thu, 01 Oct 2026 04:17:06 GMTsampleone0.1.0successhttps://mdelapi.r-universe.devhttps://github.com/mdelapi/sampleonecatalogo-formulas.Rmdcatalogo-formulas.htmlCatalogo de formulas: da apostila as funcoes do sampleone2026-09-20 21:06:482026-09-20 21:06:48