Generate ranked set sampling (RSS) on the population provided.

Usage

rss_sample(pop, n, H, K, replace = FALSE)

Arguments

pop: Population that will be sampled with an auxiliary parameter in the second column.
n: Sample size.
H: Set size for each raking group.
K: Number of rankers.
replace: A boolean which specifies whether to sample with replacement or not.

Value

A matrix with ranks from each ranker.

Examples

set.seed(112)
population_size <- 600
# the number of samples to be ranked in each set
H <- 3

replace <- FALSE
sigma <- 4
mu <- 10
n_rankers <- 3
# sample size
n <- 9

population <- qnorm((1:population_size) / (population_size + 1), mu, sigma)
rho <- 0.75
tau <- sigma * sqrt(1 / rho^2 - 1)
x <- population + tau * rnorm(population_size, 0, 1)

population <- cbind(population, x)
rss_sample(population, n, H, n_rankers, replace)
#>            [,1] [,2] [,3] [,4]
#>  [1,]  8.910625    1    3    1
#>  [2,] 12.317145    2    2    1
#>  [3,] 11.619746    3    3    2
#>  [4,]  8.307549    1    2    1
#>  [5,]  5.089992    2    2    3
#>  [6,]  7.233575    3    3    3
#>  [7,] 11.601654    1    2    2
#>  [8,]  9.134107    2    1    1
#>  [9,] 12.960431    3    3    1
#>            [,1] [,2] [,3] [,4]
#>  [1,]  8.910625    1    3    1
#>  [2,] 12.317145    2    2    1
#>  [3,] 11.619746    3    3    2
#>  [4,]  8.307549    1    2    1
#>  [5,]  5.089992    2    2    3
#>  [6,]  7.233575    3    3    3
#>  [7,] 11.601654    1    2    2
#>  [8,]  9.134107    2    1    1
#>  [9,] 12.960431    3    3    1