NormalTF {saeHB.twofold}R Documentation

Small Area Estimation Using Hierarchical Bayesian Method under Twofold Subarea Level Model with Normal distribution

Description

Usage

NormalTF(
  formula,
  vardir,
  area,
  weight,
  iter.update = 3,
  iter.mcmc = 2000,
  thin = 1,
  burn.in = 1000,
  data,
  coef,
  var.coef
)

Arguments

formula

Formula that describe the fitted model

vardir

Sampling variances of direct estimations on each subarea

area

Index that describes the code relating to area in each subarea.This should be defined for aggregation to get area estimator. Index start from 1 until m

weight

Vector contain proportion units or proportion of population on each subarea. w_{ij}

iter.update

Number of updates perform in Gibbs Sampling with default 3

iter.mcmc

Number of total iteration per chain perform in Gibbs Sampling with default 2000

thin

Thinning rate perform in Gibbs Sampling and it must be a positive integer with default 1

burn.in

Number of burn in period in Gibbs Sampling with default 1000

data

The data frame

coef

Vector contains initial value for mean on coefficient's prior distribution or \beta's prior distribution

var.coef

Vector contains Initial value for varians on coefficient's prior distribution or \beta's prior distribution

Value

This function returns a list with following objects:

Est_sub

A dataframe that contains the values, standar deviation, and quantile of Subarea mean Estimates using Twofold Subarea level model under Hierarchical Bayes method

Est_area

A dataframe that contains the values, standar deviation, and quantile of Area mean Estimates using Twofold Subarea level model under Hierarchical Bayes method

refVar

A dataframe that contains estimated subarea and area random effect variance (\sigma_{u}^{2} and \sigma_{v}^{2})

coefficient

A dataframe that contains the estimated model coefficient \beta

plot

Trace, Density, Autocorrelation Function Plot of coefficient

Examples

##load dataset for data without any nonsampled subarea
data(dataTwofold)

#formula of fitted model
formula=y~x1+x2

#model fitting
mod=NormalTF(formula,vardir="vardir",area="codearea",weight="w",data=dataTwofold)

#estimate
mod$Est_sub #Subarea mean estimate
mod$Est_area #area mean estimate
mod$coefficient #coefficient estimate
mod$refVar #random effect subarea and area estimates

#Load Library 'coda' to execute the plot
#autocorr.plot(mod$plot[[3]]) is used to generate ACF Plot
#plot(mod$plot[[3]]) is used to generate Density and trace plot

##for dataset with nonsampled subarea use dataTwofoldNS

[Package saeHB.twofold version 0.1.2 Index]