rqr_nbinom_logs

compute numerically stable negative binomial rqr

Provides a variety of Network Scale-up Models for researchers to
analyze Aggregated Relational Data, through the use of Stan and 'glmmTMB'.
Also provides tools for model checking
In this version, the package implements models from
Laga, I., Bao, L., and Niu, X (2023) <doi:10.1080/01621459.2023.2165929>,
Zheng, T., Salganik, M. J., and Gelman, A. (2006) <doi:10.1198/016214505000001168>,
Killworth, P. D., Johnsen, E. C., McCarty, C., Shelley, G. A.,
and Bernard, H. R. (1998) <doi:10.1016/S0378-8733(96)00305-X>, and
Killworth, P. D., McCarty, C., Bernard, H. R., Shelley, G. A., and
Johnsen, E. C. (1998) <doi:10.1177/0193841X9802200205>.

Ian Laga

networkscaleup

Network Scale-Up Models for Aggregated Relational Data

Owen G. Ward

Anna L. Smith

Benjamin Vogel

Jieyun Wang

Le Bao

Xiaoyue Niu

rqr_nbinom_logs function

<dl><dt>y</dt>
<dd>observed value</dd>
<dt>size</dt>
<dd>size parameter</dd>
<dt>prob</dt>
<dd>prob parameter</dd>
<dt>eps</dt>
<dd>precision parameter</dd></dl>

Arguments

compute numerically stable negative binomial rqr — rqr_nbinom_logs

<dl>

<dt>y</dt>
<dd>observed value</dd>


<dt>size</dt>
<dd>size parameter</dd>


<dt>prob</dt>
<dd>prob parameter</dd>


<dt>eps</dt>
<dd>precision parameter</dd>

</dl>

rqr_nbinom_logs: compute numerically stable negative binomial rqr

Description

Usage

Value

Arguments