samplingVarEst: Sampling Variance Estimation

Functions to calculate some point estimators and estimating their variance under unequal probability sampling without replacement. Single and two stage sampling designs are considered. Some approximations for the second order inclusion probabilities (joint inclusion probabilities) are available (sample and population based). A variety of Jackknife variance estimators are implemented. Almost every function is written in C (compiled) code for faster results. The functions incorporate some performance improvements for faster results with large datasets.

Version: 1.4
Depends: R (≥ 3.1.0)
Published: 2019-07-25
Author: Emilio Lopez Escobar [aut, cre, cph], Ernesto Barrios Zamudio [ctb], Juan Francisco Munoz Rosas [ctb]
Maintainer: Emilio Lopez Escobar <emilio at quantos.mx>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: http://www.quantos.mx, http://www.itam.mx
NeedsCompilation: yes
Classification/ACM: G.3
Classification/JEL: C13, C15, C42, C83
Classification/MSC: 62D05, 62F40, 62G09, 62H12
Citation: samplingVarEst citation info
Materials: README ChangeLog
In views: OfficialStatistics
CRAN checks: samplingVarEst results

Downloads:

Reference manual: samplingVarEst.pdf
Package source: samplingVarEst_1.4.tar.gz
Windows binaries: r-devel: samplingVarEst_1.4.zip, r-release: samplingVarEst_1.4.zip, r-oldrel: samplingVarEst_1.4.zip
macOS binaries: r-release: samplingVarEst_1.4.tgz, r-oldrel: samplingVarEst_1.4.tgz
Old sources: samplingVarEst archive

Reverse dependencies:

Reverse depends: samplingEstimates
Reverse imports: RRTCS

Linking:

Please use the canonical form https://CRAN.R-project.org/package=samplingVarEst to link to this page.