dataVill {saePseudo}

Sample Data for Small Area Estimation using Averaging Pseudo Area Level Model

Description

Dataset to simulate Small Area Estimation using Averaging Pseudo Area Level Model This data is generated by these following steps:

1. Generate population data consisting Area1 (province), Area2 (region), Area3 (sub-district), Area4 (village), and Unit. The auxiliary variabels are generated by Uniform distribution with (x1 ~ U(40, 100)) and Normal distribution with (x2 ~ N(70, 5)). The coefficient parameters are set as \beta_{0} = 0.5, \beta_{1} = 0.2, and \beta_{2} = 0.2

2. Calculate y_{k} = \beta_{0}+\beta_{1}*x1_{k}+\beta_{2}*x_2{k}

3. Generate number of sample with simple random sampling with replacement

4. Calculate ydir_area4 = \frac{\Sigma{y_{k}}}{n}, vardir_area4 = \frac{\Sigma{(y_{k}-\frac{\Sigma{y_{k}}}{n})^2}}{n-1}, and auxiliary variable X1 = \frac{\Sigma{x1_{k}}}{n}

5. Calculate N (number of population) based on the initial population generated for each Area4 selected as a sample

6. Area1, Area2, Area3, Area4, ydir_area4, vardir_area4, X1, and N are combined in a dataframe called dataVill.

Usage

dataVill

Format

A data frame with 83 observations on the following 8 variables:

Area1

Province

Area2

Region

Area3

Sub-district

Area4

Village

ydir_area4

Direct Estimation of y

vardir_area4

Sampling variance of y

X1

Auxiliary variable

N

Number of population in area4