Estimation of the Population Total under Probability Proportional to Size Sampling With Replacement
Computes the Hansen-Hurwitz estimator of the population total according to a probability proportional to size sampling with replacement design
E.PPS(y, pk)
y |
Vector, matrix or data frame containing the recollected information of the variables of interest for every unit in the selected sample |
pk |
A vector containing selection probabilities for each unit in the sample |
Returns the estimation of the population total of every single variable of interest, its estimated standard error and its estimated coefficient of variation estimated under a probability proportional to size sampling with replacement 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 random sample according to a # PPS with replacement design data(Lucy) attach(Lucy) # The selection probability of each unit is proportional to the variable Income m <- 400 res <- S.PPS(m,Income) # The selected sample sam <- res[,1] # The information about the units in the sample is stored in an object called data data <- Lucy[sam,] attach(data) names(data) # pk.s is the selection probability of each unit in the selected sample pk.s <- res[,2] # 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.PPS(estima,pk.s)
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