README.md

In iZID: Identify Zero-Inflated Distributions

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:

install.packages("iZID")

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.

iZID documentation built on Nov. 6, 2019, 5:08 p.m.