ZIPG_CI

Get confidence interval from ZIPG model

We provide a flexible Zero-inflated Poisson-Gamma Model (ZIPG) by connecting both the mean abundance and the variability to different covariates, and build valid statistical inference procedures for both parameter estimation and hypothesis testing. These functions can be used to analyze microbiome count data with zero-inflation and overdispersion. The model is discussed in Jiang et al (2023) <doi:10.1080/01621459.2022.2151447>.

Roulan Jiang

ZIPG

Zero-Inflated Poisson-Gamma Regression

Tianying Wang

ZIPG_CI function

<dl><dt>ZIPG_res</dt>
<dd>Result from ZIPG_main()</dd>
<dt>type</dt>
<dd>Type of hypothesis testing method, 'Wald' or 'bWald'.</dd>
<dt>CI_type</dt>
<dd>Type of confidence interval, 'Wald','bWald' or 'pbWald'.</dd>
<dt>alpha</dt>
<dd>We construct (1- alpha)% confidence interval by alpha/2 and (1-alpha/2).</dd></dl>

Arguments

Get confidence interval from ZIPG model — ZIPG_CI

<dl>

<dt>ZIPG_res</dt>
<dd>Result from ZIPG_main()</dd>


<dt>type</dt>
<dd>Type of hypothesis testing method, 'Wald' or 'bWald'.</dd>


<dt>CI_type</dt>
<dd>Type of confidence interval, 'Wald','bWald' or 'pbWald'.</dd>


<dt>alpha</dt>
<dd>We construct (1- alpha)% confidence interval by alpha/2 and (1-alpha/2).</dd>

</dl>

ZIPG_CI: Get confidence interval from ZIPG model

Description

Usage

Value

Arguments

Examples