Computes the Horvitz-Thompson estimator of the population total according to a BE sampling design
Vector, matrix or data frame containing the recollected information of the variables of interest for every unit in the selected sample
Inclusion probability for each unit in the population
Returns the estimation of the population total of every single variable of interest, its estimated standard error and its estimated coefficient of variation under an BE sampling design
The function returns a data matrix whose columns correspond to the estimated parameters of the variables of interest
Hugo Andres Gutierrez Rojas email@example.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.
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# Uses the Lucy data to draw a Bernoulli sample data(Lucy) attach(Lucy) N <- dim(Lucy) n=400 prob=n/N sam <- S.BE(N,prob) # The information about the units in the sample is stored in an object called data data <- Lucy[sam,] attach(data) names(data) # 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.BE(estima,prob)
The following objects are masked from Lucy: Employees, ID, Income, Level, SPAM, Taxes, Ubication, Zone  "ID" "Ubication" "Level" "Zone" "Income" "Employees"  "Taxes" "SPAM" N Income Employees Taxes Estimation 2611.640000 1.140778e+06 1.658032e+05 33762.635000 Standard Error 114.158152 6.011109e+04 8.181227e+03 2963.436852 CVE 4.371129 5.269309e+00 4.934300e+00 8.777268 DEFF Inf 3.199263e+00 4.635292e+00 1.326754
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