Est.Total.NHT {samplingVarEst} | R Documentation |
The Narain-Horvitz-Thompson estimator for a total
Description
Computes the Narain (1951); Horvitz-Thompson (1952) estimator for a population total.
Usage
Est.Total.NHT(VecY.s, VecPk.s)
Arguments
VecY.s |
vector of the variable of interest; its length is equal to |
VecPk.s |
vector of the first-order inclusion probabilities; its length is equal to |
Details
For the population total of the variable y
:
t = \sum_{k\in U} y_k
the unbiased Narain (1951); Horvitz-Thompson (1952) estimator of t
(implemented by the current function) is given by:
\hat{t}_{NHT} = \sum_{k\in s} \frac{y_k}{\pi_k}
where \pi_k
denotes the inclusion probability of the k
-th element in the sample s
.
Value
The function returns a value for the total point estimator.
Author(s)
Emilio Lopez Escobar.
References
Horvitz, D. G. and Thompson, D. J. (1952) A generalization of sampling without replacement from a finite universe. Journal of the American Statistical Association, 47, 663–685.
Narain, R. D. (1951) On sampling without replacement with varying probabilities. Journal of the Indian Society of Agricultural Statistics, 3, 169–175.
See Also
Est.Total.Hajek
VE.HT.Total.NHT
VE.SYG.Total.NHT
VE.Hajek.Total.NHT
Examples
data(oaxaca) #Loads the Oaxaca municipalities dataset
pik.U <- Pk.PropNorm.U(373, oaxaca$HOMES00) #Reconstructs the 1st order incl. probs.
s <- oaxaca$sHOMES00 #Defines the sample to be used
y1 <- oaxaca$POP10 #Defines the variable of interest y1
y2 <- oaxaca$HOMES10 #Defines the variable of interest y2
Est.Total.NHT(y1[s==1], pik.U[s==1]) #Computes the NHT estimator for y1
Est.Total.NHT(y2[s==1], pik.U[s==1]) #Computes the NHT estimator for y2