simPop package - RDocumentation

Learn R Programming

⚠️There's a newer version (2.1.3) of this package.Take me there.

simPop

This is the development place for R-package simPop

Copy Link

Version

Install

install.packages('simPop')

Monthly Downloads

385

Version

1.1.1

License

GPL (>= 2)

Issues

Pull Requests

Stars

Forks

Repository

https://github.com/statistikat/simPop

Maintainer

Matthias Templ

Last Published

May 29th, 2018

Functions in simPop (1.1.1)

correctSingleHeap

correctSingleHeap

Correct age heaping

Calibrate sample weights

Sample households from given microdata.

Calibration of 0/1 weights by Simulated Annealing

iterative proportional updating

Iterative Proportional Updating

Simulate categorical variables of population data

Utility functions for socio-economic data sets

addKnownMargins

add known margins/totals

Methods for function addWeights

Perform one step of iterative proportional updating

Compute break points for categorizing (semi-)continuous variables

get_set-methods

Extract and modify variables from population or sample data stored in an object of class simPopObj-class.

Synthetic GLSS survey data

Synthetic EU-SILC data

Synthetic EU-SILC survey data

Utility functions for EU-SILC data

Simulation of Synthetic Populations for Survey Data Considering Auxiliary Information

Simulate categorical variables of population data

Categorize (semi-)continuous variables

simPopObj-class

Class "simPopObj"

Numerical weighting functions

Simulate the household structure of population data

Simulate EU-SILC population data

Population totals Region times Gender for Austria 2006

Simulate continuous variables of population data

Plot weighted cumulative distribution functions

manageSimPopObj

get and set variables from population or sample data stored in an object of class '>simPopObj.

Simulate components of continuous variables of population data

Utility measures

Construct a matrix of binary variables for calibration

Generation of smaller regions given an existing spatial variable and a table.

Weighted sample quantiles

Mosaic plots of expected and realized population sizes

Weighted box plot statistics

Weighted cross tabulation

Sprague index (multipliers)

(Weighted empirical) cumulative distribution function

Class "dataObj"

create an object of class 'dataObj' required for further processing

Cross tabulations of expected and realized population sizes.

Synthetic EU-SILC 2013 survey data

Simple generation of new variables

Weighted box plots

weighted_estimators

Weighted mean, variance, covariance matrix and correlation matrix

Whipple index (original and modified)

Weighted contingency coefficients

Calculate mean by factors