log_mix_uniform

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

log_mix_uniform function

<dl><dt>logFl</dt>
<dd>log of lower value</dd>
<dt>logFu</dt>
<dd>log of upper value</dd></dl>

Arguments

log computed uniform quantile — log_mix_uniform

<dl>

<dt>logFl</dt>
<dd>log of lower value</dd>


<dt>logFu</dt>
<dd>log of upper value</dd>

</dl>

log computed uniform quantile

log_mix_uniform: log computed uniform quantile

Description

Usage

Value

Arguments