computeFrac: Numerical weighting functions

In surveysd: Survey Standard Error Estimation for Cumulated Estimates and their Differences in Complex Panel Designs

Numerical weighting functions

Description

Customize weight-updating within factor levels in case of numerical calibration. The functions described here serve as inputs for ipf.

Usage

computeLinear(curValue, target, x, w, boundLinear = 10)

computeLinearG1(curValue, target, x, w, boundLinear = 10)

computeFrac(curValue, target, x, w)

Arguments

curValue	Current summed up value. Same as sum(x*w)
target	Target value. An element of conP in ipf
x	Vector of numeric values to be calibrated against
w	Vector of weights
boundLinear	The output f will satisfy 1/boundLinear <= f <= boundLinear. See bound in ipf

Details

computeFrac provides the "standard" IPU updating scheme given as

f = target/curValue

which means that each weight inside the level will be multtiplied by the same factor when doing the actual update step (w := f*w). computeLinear on the other hand calculates f as

f_i = a · x_i + b

where a and b are chosen, so f satisfies the following two equations.

∑ f_i w_i x_i = target

∑ f_i w_i = ∑ w_i

computeLinearG1 calculates f in the same way as computeLinear, but if f_i*w_i<1 f_i will be set to 1/w_i.

Value

A weight multiplier f

surveysd documentation built on Dec. 28, 2022, 2:15 a.m.