E.piPS {TeachingSampling} | R Documentation |
Computes the Horvitz-Thompson estimator of the population total according to a πPS sampling design
E.piPS(y, Pik)
y |
Vector, matrix or data frame containig 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 variance and its estimated coefficient of variation under a πPPS sampling design. This function uses the results of approximate expressions for the estimated variance of the Horvitz-Thompson estimator
The function returns a data matrix whose columns correspond to the estimated parameters of the variables of interest
Hugo Andrés Gutiérrez Rojas hugogutierrez@usantotomas.edu.co
Matei, A. and Till'e, Y. (2005), Evaluation of Variance Approximations and Estimators in Maximun
Entropy Sampling with Unequal Probability and Fixed Sample Design. Journal of Official Statistics. Vol 21, 4, 543-570.
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.
# Uses the Marco and Lucy data to draw a sample according to a piPS without replacement design data(Marco) data(Lucy) attach(Lucy) # The selection probability of each unit is proportional to the variable Income # The selected sample of size n=400 n <- 400 res <- S.piPS(n, Income) 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) # Pik.s is the inclusion probability of every single unit in the selected sample Pik.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.piPS(estima,Pik.s) # Same results than HT function HT(estima, Pik.s)