E.WR: Estimation of the Population Total under Simple Random...

In TeachingSampling: Selection of Samples and Parameter Estimation in Finite Population

Description

Computes the Hansen-Hurwitz estimator of the population total according to a simple random sampling with replacement design

Usage

E.WR(N, m, y)

Arguments

N	Population size
m	Sample size
y	Vector, matrix or data frame containing 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 estimated under an simple random with replacement design

Value

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

Author(s)

Hugo Andres Gutierrez Rojas [e-mail]

References

Sarndal, C-E. and Swensson, B. and Wretman, J. (1992), Model Assisted Survey Sampling. Springer.
Gutierrez, H. A. (2009), Estrategias de muestreo: Diseno de encuestas y estimacion de parametros. Editorial Universidad Santo Tomas.

See Also

S.WR

Examples

# Uses the Lucy data to draw a random sample according to a WR design
data(Lucy)
attach(Lucy)

N <- dim(Lucy)[1]
m <- 400
sam <- S.WR(N,m)
# 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.WR(N,m,estima)

TeachingSampling documentation built on April 22, 2020, 1:05 a.m.