# iZID

iZID computes bootstrapped Monte Carlo estimate of p-value of KS test
and likelihood ratio test for zero-inflated count data based on the
previous work of Aldirawi et al. (2019). This package also enables user
to compute maximum likelihood estimate of data from standard,
zero-inflated or hurdle beta binomial, beta negative binomial, negative
binomial and Poisson distributions. Besides, user can generate random
deviates from the aforementioned distributions.

## Installation

The released version of iZID can be downloaded from CRAN with:

## Architecture

12 functions are exported from this package which can be classified
as five classes:

- bb.mle, bnb.mle, nb.mle, poisson.mle: calculate maximum likelihood
estimates for general distributions.
- bb.zihmle, bnb.zihmle, nb.zihmle, poisson.zihmle: calculate maximum
likelihood estimates for zero-inflated or hurdle distributions.
- dis.kstest: conduct one-sample KS test and output bootstrapped
p-value.
- model.lrt: conduct likelihood ratio test to compare two models and
output bootstrapped p-value.
- sample.h, sample.zi: simulate random deviates from zero-inflated or
hurdle models.