E.SI {TeachingSampling}R Documentation

Estimation of the Population Total under Simple Random Sampling Without Replacement

Description

Computes the Horvitz-Thompson estimator of the population total according to an SI sampling design

Usage

E.SI(N, n, y)

Arguments

N Population size
n Sample size
y Vector, matrix or data frame containig the recollected information of the variables of interest for every unit in the 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 under an SI sampling design

Value

The function returns a data matrix whose columns correspond to the estimated parameters of the variables of interest

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.SI

Examples

############
## Example 1
############
# Uses the Marco Lucy data to draw a random sample of units according to a SI design
data(Marco)
data(Lucy)

N <- dim(Marco)[1]
n <- 400
sam <- S.SI(N,n)
# 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.SI(N,n,estima)

############
## Example 2
############
# Following with Example 1. The variable SPAM is a domain of interest
Doma <- Domains(SPAM)
# This function allows to estimate the parameters of the variables of interest 
# for every category in the domain SPAM
estima <- data.frame(Income, Employees, Taxes)
SPAM.no <- estima*Doma[,1]
SPAM.yes <- estima*Doma[,2]
E.SI(N,n,SPAM.no)
E.SI(N,n,SPAM.yes)

[Package TeachingSampling version 0.7.6 Index]