E.STPPS {TeachingSampling}R Documentation

Estimation of the Population Total under Stratified Probability Proportional to Size Sampling With Replacement

Description

Computes the Hansen-Hurwitz estimator of the population total according to a probability proportional to size sampling with replacement design

Usage

E.STPPS(y, pk, mh, S)

Arguments

y Vector, matrix or data frame containig the recollected information of the variables of interest for every unit in the selected sample
pk A vetor containing selection probabilities for each unit in the sample
mh Vector of sample size in each stratum
S Vector identifying the membership to the strata of each unit in selected sample

Details

Returns the estimation of the population total of every single variable of interest, its estimated variance and its estimated coefficient of variation in all of the stratum and finally in the entire population

Value

The function returns an array composed by several matrices representing each varible of interest. The columns of each matrix correspond to the estimated parameters of the variables of interest in each stratum and in the entire population

Author(s)

Hugo Andrés Gutiérrez Rojas hugogutierrez@usantotomas.edu.co

References

Sarndal, C-E. and Swensson, B. and Wretman, J. (1992), Model Assisted Survey Sampling. Springer.
Guti'errez, H. A. (2009), Estrategias de muestreo: Dise~no de encuestas y estimaci'on de par'ametros. Editorial Universidad Santo Tom'as.

See Also

S.STPPS

Examples

# Uses the Marco and Lucy data to draw a stratified random sample 
# according to a SI design in each stratum
data(Marco)
data(Lucy)
attach(Lucy)
# Level is the stratifying variable
summary(Level)
# Defines the sample size at each stratum
m1<-14
m2<-123
m3<-263
mh<-c(m1,m2,m3)
# Draws a stratified sample
res<-S.STPPS(Level, Income, mh)
# The selected sample
sam<-res[,1]
# The selection probability of each unit in the selected sample
pk <- res[,2]
pk
# The information about the units in the sample is stored in an object called data
data <- Lucy[sam,]
attach(data)
names(data)
# The variables of interest are: Income, Employees and Taxes
# This information is stored in a data frame called estima
estima <- data.frame(Income, Employees, Taxes)
E.STPPS(estima,pk,mh,Level)

[Package TeachingSampling version 0.7.6 Index]