NonProbEst

0.2.4

Estimation in Nonprobability Sampling

0packages depend

2.7Kdownloads / year

–test coverage

9/13checks pass

Overview

About

Maintained by Luis Castro MartínFirst published 2019-06-186 releasesCRAN page ↗

Different inference procedures are proposed in the literature to correct for selection bias that might be introduced with non-random selection mechanisms. A class of methods to correct for selection bias is to apply a statistical model to predict the units not in the sample (super-population modeling). Other studies use calibration or Statistical Matching (statistically match nonprobability and probability samples). To date, the more relevant methods are weighting by Propensity Score Adjustment (PSA). The Propensity Score Adjustment method was originally developed to construct weights by estimating response probabilities and using them in Horvitz–Thompson type estimators. This method is usually used by combining a non-probability sample with a reference sample to construct propensity models for the non-probability sample. Calibration can be used in a posterior way to adding information of auxiliary variables. Propensity scores in PSA are usually estimated using logistic regression models. Machine learning classification algorithms can be used as alternatives for logistic regression as a technique to estimate propensities. The package 'NonProbEst' implements some of these methods and thus provides a wide options to work with data coming from a non-probabilistic sample.

Install

R (CRAN)Ubuntu (r2u)Fedora (COPR)openSUSE (OBS)

install.packages("NonProbEst", repos = "https://cloud.r-project.org/")

Installs the current CRAN release. Prebuilt binaries on Windows and macOS.

Release

# enable cranapt (r2u) if it is not already set up, then install
grep -rqs r2u.stat.illinois.edu /etc/apt/sources.list /etc/apt/sources.list.d/ \
  || curl -fsSL https://raw.githubusercontent.com/eddelbuettel/r2u/master/inst/scripts/add_cranapt_noble.sh | sudo bash
sudo apt install -y r-cran-nonprobest

Fast Ubuntu binaries via r2u (no compilation). The cranapt setup runs once and is skipped when it is already enabled.

bspm (used by r2u) also needs make: sudo apt install make

# enable the iucar/cran COPR if it is not already present, then install
ls /etc/yum.repos.d/*iucar*cran*.repo >/dev/null 2>&1 \
  || sudo dnf copr enable -y iucar/cran
sudo dnf install -y R-CRAN-NonProbEst

RPMs from the iucar/cran COPR, rebuilt from CRAN.

For install.packages() integration in R, also: sudo dnf install R-CoprManager

# add the autoCRAN OBS repo (Tumbleweed) if it is missing, then install
zypper -q lr | grep -qi autoCRAN \
  || sudo zypper addrepo https://download.opensuse.org/repositories/devel:/languages:/R:/autoCRAN/openSUSE_Tumbleweed/devel:languages:R:autoCRAN.repo
sudo zypper install -y R-NonProbEst

RPMs auto-built from CRAN on openSUSE OBS (Tumbleweed).

Health

CRAN checks

4NOTE9OK

Failing flavors

NOTE r-devel-linux-x86_64-debian-clang
NOTE r-devel-linux-x86_64-debian-gcc
NOTE r-devel-linux-x86_64-fedora-clang
NOTE r-devel-linux-x86_64-fedora-gcc

Slowest check: 4.0 min · r-devel-linux-x86_64-fedora-clang

Code health

None

Tests · ratio 0.00

not tracked

Coverage

Dependencies · direct

Check history

NOTE2026-06-09
9 OK · 4 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
ERROR2026-06-08
9 OK · 3 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
NOTE2026-05-02
9 OK · 4 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
ERROR2026-04-25
7 OK · 4 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
NOTE2026-03-10
10 OK · 4 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE

Documentation

READMENoVignettesNopkgdown siteNoNEWSNoCode of conductNoContributing guideNo

Examples that run: 88%
Documented parameters: not tracked
Return-value docs: not tracked
References docs: 75%

Downloads

2.7K

CRAN downloads in the past year

Rank #14,774 · ~7/day · ~227/mo

Releases R versions

Daily download trend is not available in this view yet.

22230 days

75390 days

2.7K1 year

Compare downloads with other packages →

Also on96 r2u17 autocran14 c2d4u

Dependencies

Declared dependencies

4 external dependencies (excludes base and recommended)

Depends (0)

none

Imports (5)

caret sampling e1071 glmnetMatrix

LinkingTo (0)

none

Suggests (0)

none

Enhances (0)

none

Dependency license breakdown →

Reverse dependencies

0direct

0indirect

Nothing depends on this yet.

Code & Tests

Code Composition

Rd 826 (57%)R 623 (43%)

Code characteristics

Cyclomatic complexity: 1.0 median / 6 max

Test coverage

Line coverage

–

Expression

–

Tests / Examples

–

Functions

17 0 exported

Complexity

1.9 avg / 6 max

Call network

17 nodes / 8 edges

Call graph

Open call graph →

Loading call graph…

Lowest coverage

Per-function coverage is not measured for this package yet.

Datasets

Bundled datasets · 3

Name	Class	Rows × Cols	Also ships in
population	data.frame	50,000 × 6	–
sampleNP	data.frame	1,000 × 9	–
sampleP	data.frame	500 × 5	–

People & History

People (0)

Author records are not tracked yet for this package.

Listed in earlier versions (3)

Ramón Ferri García

no longer listed · 0.1.0 to 0.2.4

Luis Castro Martín

no longer listed · 0.1.0 to 0.2.4

María del Mar Rueda

no longer listed · 0.1.0 to 0.2.4

Package Timeline

6 releases. Pick two to compare their code metrics. R releases are shown for context.

R
R 4.6.0 released · 2026-04-24
R
R 4.5.0 released · 2025-04-11
R
R 4.4.0 released · 2024-04-24
R
R 4.3.0 released · 2023-04-21
R
R 4.2.0 released · 2022-04-22
R
R 4.1.0 released · 2021-05-18
0.2.4Latest
2020-06-03 · current release · diff ↗
R
R 4.0.0 released · 2020-04-24
0.2.3
2019-12-17 · diff ↗
0.2.2
2019-11-29 · diff ↗
0.2.1
2019-09-30 · diff ↗
0.2.0
2019-09-07 · diff ↗
0.1.0
2019-06-18
R
R 3.6.0 released · 2019-04-26

Package metadata

First published: 2019-06-18
Total releases: 6 / 7 yrs
License: GPL (>= 2) OSI
Bundled data: 124 KB / 3 files
Download size: 138 KB
Installed size: not tracked yet
With dependencies: not tracked yet

Appears in task views

Official Statistics & Survey Statistics

Report a problem with this page →