S.BE {TeachingSampling} | R Documentation |
Bernoulli Sampling Without Replacement
Description
Draws a Bernoulli sample without replacement of expected size $n$ from a population of size $N$
Usage
S.BE(N, prob)
Arguments
N |
Population size |
prob |
Inclusion probability for each unit in the population |
Details
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.
Value
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.
Author(s)
Hugo Andres Gutierrez Rojas hagutierrezro@gmail.com
References
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.
See Also
Examples
############
## Example 1
############
# 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]
############
## Example 2
############
# 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)