E_negbin_noinfl

Computes the expected value from a zero-truncated negative binomial (ZTNB) distribution 
based on the model parameters and covariates.

internal

Estimates one-inflated positive Poisson (OIPP) and
one-inflated zero-truncated negative binomial (OIZTNB) regression
models. A suite of ancillary statistical tools are also provided,
including: estimation of positive Poisson (PP) and zero-truncated
negative binomial (ZTNB) models; marginal effects and their standard
errors; diagnostic likelihood ratio and Wald tests; plotting;
predicted counts and expected responses; and random variate
generation. The models and tools, as well as four applications, are
shown in Godwin, R. T. (2024). "One-inflated zero-truncated count
regression models" arXiv preprint <doi:10.48550/arXiv.2402.02272>.

Ryan T. Godwin

oneinfl

Estimates OIPP and OIZTNB Regression Models

E_negbin_noinfl function

<dl><dt>b</dt>
<dd>Numeric vector of coefficients for the regression model.</dd>
<dt>a</dt>
<dd>Numeric scalar, the overdispersion parameter of the negative binomial distribution.</dd>
<dt>X</dt>
<dd>Matrix of predictors for the model, where rows correspond to observations 
and columns to covariates.</dd></dl>

Arguments

Expected Value for Zero-Truncated Negative Binomial Distribution — E_negbin_noinfl

<dl>

<dt>b</dt>
<dd>Numeric vector of coefficients for the regression model.</dd>


<dt>a</dt>
<dd>Numeric scalar, the overdispersion parameter of the negative binomial distribution.</dd>


<dt>X</dt>
<dd>Matrix of predictors for the model, where rows correspond to observations 
and columns to covariates.</dd>

</dl>

E_negbin_noinfl: Expected Value for Zero-Truncated Negative Binomial Distribution

Description

Usage

Value

Arguments

See Also