dataTwofold {saeHB.twofold}R Documentation

Simulated dataset Under Two Fold Subarea level model with Normal distribution.

Description

A dataset to simulate Small Area Estimation using Hierarchical Bayesian method under Two Fold Subarea level model with Normal distribution on variabel interest.

This data is generated by these following steps:

  1. Generate sampling error e_{ij},subarea random effect u_{ij}, area random effect v_{i}, auxiliary variabel x_{ij1},x_{ij2}, and weight or proportions of unit w_{ij}

    • Generate subarea random effect u_{ij}~N(0,8)

    • Generate area random effect v_{i} ~ N(0,8)

    • Generate auxilary variabel on subarea level x_{ij1}~ U(0,1)

    • Generate auxilary variabel on subarea level x_{ij2}~N(10,1)

    • Generate unit proportion on each subarea w_{ij}~U(10,20)

    • Generate sampling error e_{ij}~N(0,\sigma^{2}_{e}) where \sigma^{2}_{e}~IG(1,1) is a variance of direct estimator

    • Setting coefficient \beta_{0}=\beta_{1}=\beta_{2} =1

    • Calculate target parameter \mu_{ij}=\beta_{0} +\beta_{1}x_{ij1} +\beta_{2}x_{ij2}+v_{i}+u_{ij}

    • Calculate direct estimator y_{ij}=\mu_{ij}+e_{ij}

  2. Auxiliary variables x_{ij1},x_{ij2}, direct estimation (y_{ij}) ,vardir, and weight w_{ij} are combined in a dataframe called dataTwofold

Usage

dataTwofold

Format

A data frame with 90 rows and 6 columns:

y

Direct estimation of subarea mean y_{ij}

x1

Auxiliary variabel of x_{ij1}

x2

Auxiliary variabel of x_{ij2}

codearea

Index that describes the code relating to warea for each subarea

w

Unit proportion on each subarea or weight w_{ij}

vardir

Sampling variance of direct estimator y_{ij}


[Package saeHB.twofold version 0.1.2 Index]