Wk {TeachingSampling} | R Documentation |
Computes the calibration weights for the estimation of the population total of several variables of interest
Wk(x,tx,Pik,ck)
x |
Vector, matrix or data frame containig the recollected auxiliary information for every unit in the selected sample |
tx |
Vector containing the populations totals of the auxiliary information |
Pik |
A vetor containing inclusion probabilities for each unit in the sample |
ck |
A vector of weights induced by the structure of variance of the supposed model |
The calibration weights satisfy the following expression
sum_{kin S}w_kx_k=sum_{kin U}x_k
The function returns a matrix of calibrated weights.
Hugo Andrés Gutiérrez Rojas hugogutierrez@usantotomas.edu.co
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
############ ## Example 1 ############ # Draws a simple random sample without replacement data(Marco) data(Lucy) dim(Marco) N <- dim(Marco)[1] n <- 400 sam <- sample(N,n) # The information about the units in the sample is stored in an object called data data <- Lucy[sam,] attach(data) names(data) # Vector of inclusion probabilities Pik<-rep(n/N,n) ############################## x <- rep(1,n) ck <- rep(1,n) tx <- c(N) wk <- Wk(x,tx,Pik,ck) sum(wk*x) ############################## x <- Employees tx <- c(151950) ck <- x wk <- Wk(x,tx,Pik,ck) sum(wk*x) ############################## x <- Taxes tx <- c(28654) ck <- rep(1,n) wk <- Wk(x,tx,Pik,ck) sum(wk*x) ############################## x <- data.frame(Employees, Taxes) tx <- c(151950, 28654) ck <- matrix(1, n, 2) wk <- Wk(x,tx,Pik,ck) sum(wk[,1]*x[,1]) sum(wk[,1]*x[,2]) sum(wk[,2]*x[,2]) sum(wk[,2]*x[,1]) ############################## x <- data.frame(Employees, Taxes) tx <- c(151950, 28654) ck <- x wk <- Wk(x,tx,Pik,ck) sum(wk[,1]*x[,1]) sum(wk[,1]*x[,2]) sum(wk[,2]*x[,2]) sum(wk[,2]*x[,1]) ############################## x <- cbind(1,Taxes) tx <- c(N,28654) ck <- x wk <- Wk(x,tx,Pik,ck) sum(wk[,1]*x[,1]) sum(wk[,1]*x[,2]) sum(wk[,2]*x[,2]) sum(wk[,2]*x[,1])