Domains {TeachingSampling} | R Documentation |
Domains Indicator Matrix
Description
Creates a matrix of domain indicator variables for every single unit in the selected sample or in the entire population
Usage
Domains(y)
Arguments
y |
Vector of the domain of interest containing the membership of each unit to a specified category of the domain |
Details
Each value of y represents the domain which a specified unit belongs
Value
The function returns a n\times p
matrix, where n
is the number of units in the selected
sample and p
is the number of categories of the domain of interest. The values of this matrix are zero, if the unit does not
belongs to a specified category and one, otherwise.
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.
See Also
Examples
############
## Example 1
############
# This domain contains only two categories: "yes" and "no"
x <- as.factor(c("yes","yes","yes","no","no","no","no","yes","yes"))
Domains(x)
############
## Example 2
############
# Uses the Lucy data to draw a random sample of units according
# to a SI design
data(Lucy)
attach(Lucy)
N <- dim(Lucy)[1]
n <- 400
sam <- sample(N,n)
# The information about the units in the sample is stored in an object called data
data <- Lucy[sam,]
attach(data)
names(data)
# The variable SPAM is a domain of interest
Doma <- Domains(SPAM)
Doma
# HT estimation of the absolute domain size for every category in the domain
# of interest
E.SI(N,n,Doma)
############
## Example 3
############
# Following with Example 2...
# The variables of interest are: Income, Employees and Taxes
# This function allows to estimate the population total of this variables for every
# category in the domain of interest SPAM
estima <- data.frame(Income, Employees, Taxes)
SPAM.no <- estima*Doma[,1]
SPAM.yes <- estima*Doma[,2]
E.SI(N,n,SPAM.no)
E.SI(N,n,SPAM.yes)