Sampling Support for Random Size Without Replacement Sampling Designs
Creates a matrix containing every possible sample under random sample size designs
SupportRS(N, ID=FALSE)
N |
Population size |
ID |
By default FALSE, a vector of values (numeric or string) identifying each unit in the population |
A support is defined as the set of samples such that for any sample in the support, all the permutations of the coordinates of the sample are also in the support
The function returns a matrix of 2^N rows and N columns. Each row of this matrix corresponds to a possible sample
Hugo Andres Gutierrez Rojas hagutierrezro@gmail.com
Tille, Y. (2006), Sampling Algorithms. Springer
Gutierrez, H. A. (2009), Estrategias de muestreo: Diseno de encuestas y estimacion de parametros.
Editorial Universidad Santo Tomas
# Vector U contains the label of a population
U <- c("Yves", "Ken", "Erik", "Sharon", "Leslie")
N <- length(U)
# The support for fixed size without replacement sampling designs
# Under this context, there are ten (10) possibles samples
SupportRS(N)
# The same support, but labeled
SupportRS(N, ID=U)
# y is the variable of interest
y<-c(32,34,46,89,35)
# The following output is very useful when checking
# the design-unbiasedness of an estimator
SupportRS(N, ID=y)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.