dataME {saeME}

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