TeachingSampling (version 4.1.1)

E.PO: Estimation of the Population Total under Poisson Sampling Without Replacement

Description

Computes the Horvitz-Thompson estimator of the population total according to a PO sampling design

Usage

E.PO(y, Pik)

Arguments

y

Vector, matrix or data frame containing the recollected information of the variables of interest for every unit in the selected sample

Pik

Vector of inclusion probabilities for each unit in the selected sample

Value

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

Details

Returns the estimation of the population total of every single variable of interest, its estimated standard error and its estimated coefficient of variation under a PO sampling design

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.PO

Examples

# NOT RUN {
# Uses the Lucy data to draw a Poisson sample
data(Lucy)
attach(Lucy)
N <- dim(Lucy)[1]
# The population size is 2396. The expected sample size is 400
# The inclusion probability is proportional to the variable Income
n <- 400
Pik<-n*Income/sum(Income)
# The selected sample
sam <- S.PO(N,Pik)
# The information about the units in the sample is stored in an object called data
data <- Lucy[sam,]
attach(data)
names(data)
# The inclusion probabilities of each unit in the selected smaple
inclusion <- Pik[sam]
# 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.PO(estima,inclusion)
# }