samplingVarEst-package: Sampling Variance Estimation package

Description

The package contains functions to calculate some point estimators and estimating their variance under unequal probability sampling without replacement. Uni-stage and two-stage sampling designs are considered. The package further contains some approximations for the joint-inclusion probabilities (population and sample based formulae).

Emphasis has been put on the speed of routines as the package mostly uses C compiled code. Below there is a list of available functions. These are grouped in purpose-lists, aiming to clarify their usage.

The user should pick a suitable combination of: a population parameter of interest, a choice of point estimator, and a choice of variance estimator.

For these population parameters:	The available point estimators are:
total:	`Est.Total.NHT`
	`Est.Total.Hajek`
mean:	`Est.Mean.NHT`
	`Est.Mean.Hajek`
empirical cumulative distribution function:	`Est.EmpDistFunc.NHT`
	`Est.EmpDistFunc.Hajek`
ratio:	`Est.Ratio`
correlation coefficient:	`Est.Corr.NHT`
	`Est.Corr.Hajek`
regression coefficients:	`Est.RegCoI.Hajek`
	`Est.RegCo.Hajek`

For these point estimators:	The available variance estimators for uni-stage samples are:
`Est.Total.NHT`:	`VE.HT.Total.NHT`
	`VE.SYG.Total.NHT`
	`VE.Hajek.Total.NHT`
`Est.Total.Hajek`:	`VE.Jk.Tukey.Total.Hajek`
	`VE.Jk.CBS.HT.Total.Hajek`
	`VE.Jk.CBS.SYG.Total.Hajek`
	`VE.Jk.B.Total.Hajek`
	`VE.EB.HT.Total.Hajek`
	`VE.EB.SYG.Total.Hajek`
`Est.Mean.NHT`:	`VE.HT.Mean.NHT`
	`VE.SYG.Mean.NHT`
	`VE.Hajek.Mean.NHT`
`Est.Mean.Hajek`:	`VE.Jk.Tukey.Mean.Hajek`
	`VE.Jk.CBS.HT.Mean.Hajek`
	`VE.Jk.CBS.SYG.Mean.Hajek`
	`VE.Jk.B.Mean.Hajek`
	`VE.EB.HT.Mean.Hajek`
	`VE.EB.SYG.Mean.Hajek`
`Est.Ratio`:	`VE.Lin.HT.Ratio`
	`VE.Lin.SYG.Ratio`
	`VE.Jk.Tukey.Ratio`
	`VE.Jk.CBS.HT.Ratio`
	`VE.Jk.CBS.SYG.Ratio`
	`VE.Jk.B.Ratio`
	`VE.EB.HT.Ratio`
	`VE.EB.SYG.Ratio`
`Est.Corr.NHT`:	`VE.Jk.Tukey.Corr.NHT`
`Est.Corr.Hajek`:	`VE.Jk.Tukey.Corr.Hajek`
	`VE.Jk.CBS.HT.Corr.Hajek`
	`VE.Jk.CBS.SYG.Corr.Hajek`
	`VE.Jk.B.Corr.Hajek`
`Est.RegCoI.Hajek`:	`VE.Jk.Tukey.RegCoI.Hajek`
	`VE.Jk.CBS.HT.RegCoI.Hajek`
	`VE.Jk.CBS.SYG.RegCoI.Hajek`
	`VE.Jk.B.RegCoI.Hajek`
`Est.RegCo.Hajek`:	`VE.Jk.Tukey.RegCo.Hajek`
	`VE.Jk.CBS.HT.RegCo.Hajek`
	`VE.Jk.CBS.SYG.RegCo.Hajek`
	`VE.Jk.B.RegCo.Hajek`

For these point estimators:	The available variance estimators for self-weighted two-stage samples are:
`Est.Total.Hajek`:	`VE.Jk.EB.SW2.Total.Hajek`
`Est.Mean.Hajek`:	`VE.Jk.EB.SW2.Mean.Hajek`
`Est.Ratio`:	`VE.Jk.EB.SW2.Ratio`
`Est.Corr.Hajek`:	`VE.Jk.EB.SW2.Corr.Hajek`
`Est.RegCoI.Hajek`:	`VE.Jk.EB.SW2.RegCoI.Hajek`
`Est.RegCo.Hajek`:	`VE.Jk.EB.SW2.RegCo.Hajek`

For the inclusion probabilities:	The available functions are:
1st order inclusion probabilities:	`Pk.PropNorm.U`
2nd order (joint) inclusion probabilities:	`Pkl.Hajek.s`
	`Pkl.Hajek.U`

datasets

oaxaca

Arguments

Details

To return to this description type:
help(samplingVarEst)
or type:
?samplingVarEst
To cite, use:
citation("samplingVarEst")