Description Usage Arguments Details Value Author(s) References See Also Examples

Creates a matrix containing every possible sample under fixed sample size with replacement designs

1 |

`N` |
Population size |

`m` |
Sample 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 *binom(N+m-1)(m)* rows and *m* columns. Each row of this matrix
corresponds to a possible sample

Hugo Andres Gutierrez Rojas hagutierrezro@gmail.com

Ortiz, J. E. (2009), *Simulacion y metodos estadisticos*. Editorial Universidad Santo Tomas.

Tille, Y. (2006), *Sampling Algorithms*. Springer.

Gutierrez, H. A. (2009), *Estrategias de muestreo: Diseno de encuestas y estimacion de parametros*.
Editorial Universidad Santo Tomas.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 | ```
# Vector U contains the label of a population
U <- c("Yves", "Ken", "Erik", "Sharon", "Leslie")
N <- length(U)
m <- 2
# The support for fixed size without replacement sampling designs
# Under this context, there are ten (10) possibles samples
SupportWR(N, m)
# The same support, but labeled
SupportWR(N, m, 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
SupportWR(N, m, ID=y)
``` |

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