Bernoulli Sampling Without Replacement
Draws a Bernoulli sample without replacement of expected size $n$ from a population of size $N$
S.BE(N, prob)
N |
Population size |
prob |
Inclusion probability for each unit in the population |
The selected sample is drawn according to a sequential procedure algorithm based on an uniform distribution. The Bernoulli sampling design is not a fixed sample size one.
The function returns a vector of size N. Each element of this vector indicates if the unit was selected. Then, if the value of this vector for unit k is zero, the unit k was not selected in the sample; otherwise, the unit was selected in the sample.
Hugo Andres Gutierrez Rojas hagutierrezro@gmail.com
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.
Tille, Y. (2006), Sampling Algorithms. Springer.
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## Example 1
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# Vector U contains the label of a population of size N=5
U <- c("Yves", "Ken", "Erik", "Sharon", "Leslie")
# Draws a Bernoulli sample without replacement of expected size n=3
# The inlusion probability is 0.6 for each unit in the population
sam <- S.BE(5,0.6)
sam
# The selected sample is
U[sam]
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## Example 2
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# Uses the Lucy data to draw a Bernoulli sample
data(Lucy)
attach(Lucy)
N <- dim(Lucy)[1]
# The population size is 2396. If the expected sample size is 400
# then, the inclusion probability must be 400/2396=0.1669
sam <- S.BE(N,0.01669)
# The information about the units in the sample is stored in an object called data
data <- Lucy[sam,]
data
dim(data)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.