GPois: Small Area Estimation Using Hierarchical Bayesian Method...

In joiceevangelista/saeHB.gpois: SAE using HB Method under Generalized Poisson Distribution

Small Area Estimation Using Hierarchical Bayesian Method under Generalized Poisson Distribution

Description

This function is implemented to variable of interest (y) that assumed to be a Generalized Poisson Distribution. The range of data is 0 < y < ∞. Generalized Distribution model can be used to handle underdispersion and overdispersion in count data.

Usage

GPois(
  formula,
  iter.update = 3,
  iter.mcmc = 2000,
  coef,
  var.coef,
  thin = 1,
  burn.in = 1000,
  tau.u = 1,
  data
)

Arguments

formula	Formula that describe the fitted model
iter.update	Number of updates with default 3
iter.mcmc	Number of total iterations per chain with default 2000
coef	Regression coefficient for variable of interest (y)
var.coef	Variance of coefficient
thin	Thinning rate, must be a positive integer with default 1
burn.in	Number of iterations to discard at the beginning with default 1000
tau.u	Variance of random effect area for non-zero count of variable interest with default 1
data	The data frame

Value

This function returns a list of the following objects:

Est	A vector with the values of Small Area mean Estimates using Hierarchical Bayesian method
refVar	Estimated random effect variances
coefficient	A dataframe contains the estimated model coefficient
plot	Trace, Density, Autocorrelation Function Plot of MCMC samples

Examples

##For data without any non-sampled area
data(dataGPois)     # Load dataset

result <- GPois(y ~ x1 + x2, data = dataGPois)

result$Est           # Small Area mean estimates
result$refVar        # Estimated random effect variances
result$coefficient   # Estimated model coefficient

# Load library 'coda' to execute the plot
# autocorr.plot(result$plot[[3]])  # Generate ACF Plot
# plot(result$plot[[3]])           # Generate Density and Trace Plot

## For data with non-sampled area use dataGPoisNs

joiceevangelista/saeHB.gpois documentation built on June 15, 2022, 9:56 a.m.