In niroshar/hglmbc: Small Area Estimation Using h-likelihood with Bias Correction for generalized class of distributions

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/README-",
  out.width = "100%"
)

hglmbc

This R package is built to apply h-likelihood approach with bias correction to make inferences in Small Area Estimation. The model parameters are obtained through an iterative approximation based on Newton Raphson method. The bias correction approach enhances the accuracy of maximum hierarchical likelihood estimates (MHLEs). This R package can be used to obtain improved MHLEs for fixed effects, random effects, and dispersion parameters for exponential family distributions with random effect u being normally distributed.

Installation

You can install the released version of hglmbc from CRAN with:

install.packages("hglmbc")

Example

This is a basic example which shows you how to solve a common problem:

library(hglmbc)
## basic example code

What is special about using README.Rmd instead of just README.md? You can include R chunks like so:

summary(cars)

You'll still need to render README.Rmd regularly, to keep README.md up-to-date.

You can also embed plots, for example:

plot(pressure)

In that case, don't forget to commit and push the resulting figure files, so they display on GitHub!

niroshar/hglmbc documentation built on June 15, 2020, 12:40 a.m.