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

Computes the Horvitz-Thompson estimator of the population total according to a PO sampling design

1 |

`y` |
Vector, matrix or data frame containing 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 standard error and its estimated coefficient of variation under a PO sampling design

The function returns a data matrix whose columns correspond to the estimated parameters of the variables of interest

Hugo Andres Gutierrez Rojas hugogutierrez@usantotomas.edu.co

Sarndal, C-E. and Swensson, B. and Wretman, J. (1992), *Model Assisted Survey Sampling*. Springer.

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

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# Uses the Lucy data to draw a Poisson sample
data(Lucy)
attach(Lucy)
N <- dim(Lucy)[1]
# The population size is 2396. The expected sample size is 400
# The inclusion probability is proportional to the variable Income
n <- 400
Pik<-n*Income/sum(Income)
# The selected sample
sam <- S.PO(N,Pik)
# The information about the units in the sample is stored in an object called data
data <- Lucy[sam,]
attach(data)
names(data)
# The inclusion probabilities of each unit in the selected smaple
inclusion <- Pik[sam]
# 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.PO(estima,inclusion)
``` |

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