Estimation of the Population Total under Poisson Sampling Without Replacement
Computes the Horvitz-Thompson estimator of the population total according to a PO sampling design
E.PO(y, Pik)
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 |
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
The function returns a data matrix whose columns correspond to the estimated parameters of the variables of interest
Hugo Andres Gutierrez Rojas hagutierrezro@gmail.com
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.
# 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)
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