dataME: dataME

In saeME: Small Area Estimation with Measurement Error

dataME

Description

This data generated by simulation based on Fay-Herriot with Measurement Error Model by following these steps:

1. Generate x_{i} from a UNIF(5, 10) distribution, \psi_{i} = 3, c_{i} = 0.25, and \sigma_{v}^{2} = 2.

2. Generate u_{i} from a N(0, c_{i}) distribution, e_{i} from a N(0, \psi_{i}) distribution, and v_{i} from a N(0, \sigma_{v}^{2}) distribution.

3. Generate \hat{x}_{i} = x_{i} + u_{i}.

4. Then for each iteration, we generated Y_{i} = 2 + 0.5 \hat{x}_{i} + v_{i} and y_{i} = Y_{i} + e_{i}.

Direct estimator y, auxiliary variable \hat{x}, sampling variance \psi, and c are arranged in a dataframe called dataME.

Usage

data(dataME)

Format

A data frame with 100 observations on the following 4 variables.

small_area

areas of interest.

y

direct estimator for each domain.

x.hat

auxiliary variable for each domain.

vardir

sampling variances for each domain.

var.x

mean squared error of auxiliary variable and sorted as x.hat

saeME documentation built on Aug. 21, 2023, 9:07 a.m.