actors

The related data files 'events', 'same_location', 'same_culture' contain
information on the event sequence and the two event statistics respectively.

datasets

Implementation of default Bayes factors
for testing statistical hypotheses under various statistical models. The package is
intended for applied quantitative researchers in the
social and behavioral sciences, medical research,
and related fields. The Bayes factor tests can be
executed for statistical models such as
univariate and multivariate normal linear models,
correlation analysis, generalized linear models, special cases of
linear mixed models, survival models, relational
event models. Parameters that can be tested are
location parameters (e.g., group means, regression coefficients),
variances (e.g., group variances), and measures of
association (e.g,. polychoric/polyserial/biserial/tetrachoric/product
moments correlations), among others.
The statistical underpinnings are
described in
Mulder and Xin (2019) <DOI:10.1080/00273171.2021.1904809>,
Mulder and Gelissen (2019) <DOI:10.1080/02664763.2021.1992360>,
Mulder (2016) <DOI:10.1016/j.jmp.2014.09.004>,
Mulder and Fox (2019) <DOI:10.1214/18-BA1115>,
Mulder and Fox (2013) <DOI:10.1007/s11222-011-9295-3>,
Boeing-Messing, van Assen, Hofman, Hoijtink, and Mulder (2017) <DOI:10.1037/met0000116>,
Hoijtink, Mulder, van Lissa, and Gu, (2018) <DOI:10.31234/osf.io/v3shc>,
Gu, Mulder, and Hoijtink, (2018) <DOI:10.1111/bmsp.12110>,
Hoijtink, Gu, and Mulder, (2018) <DOI:10.1111/bmsp.12145>, and
Hoijtink, Gu, Mulder, and Rosseel, (2018) <DOI:10.1037/met0000187>. When using the
packages, please refer to Mulder et al. (2021) <DOI:10.18637/jss.v100.i18>.

Joris Mulder

BFpack

Flexible Bayes Factor Testing of Scientific Expectations

Caspar van Lissa

Donald R. Williams

Xin Gu

Anton Olsson-Collentine

Florian Boeing-Messing

Jean-Paul Fox

Janosch Menke

Robbie van Aert

Barry Brown

James Lovato

Kathy Russell

Lapack 3.8 

Jack Dongarra

Jim Bunch

Cleve Moler

Gilbert Stewart

John Burkandt

Ashwith Rego

Alexander Godunov

Alan Miller

Jean-Pierre Moreau

The R Core Team 

actors function

dataframe (25 rows, 4 columns)
<table class="table">
<tr><td>actors$id</td><td><code>integer</code></td><td>ID of the employee, corresponding to
 the sender and receiver IDs in the events dataframe</td></tr>
<tr><td>actors$location</td><td><code>numeric</code></td><td>Location of the actor,
 ranging from 1-4</td></tr>
<tr><td>actors$culture</td><td><code>character</code></td><td>Categorical variable, indicating the
 culture of the employee</td></tr>
</table>

Format

Actors from a small hypothetical network — actors

dataframe (25 rows, 4 columns)
<table class='table'>
<tr><td>actors$id</td><td><code>integer</code></td><td>ID of the employee, corresponding to
 the sender and receiver IDs in the events dataframe</td></tr>
<tr><td>actors$location</td><td><code>numeric</code></td><td>Location of the actor,
 ranging from 1-4</td></tr>
<tr><td>actors$culture</td><td><code>character</code></td><td>Categorical variable, indicating the
 culture of the employee</td></tr>
</table>

Actors from a small hypothetical network

actors$id	`integer`	ID of the employee, corresponding to the sender and receiver IDs in the events dataframe
actors$location	`numeric`	Location of the actor, ranging from 1-4
actors$culture	`character`	Categorical variable, indicating the culture of the employee

actors: Actors from a small hypothetical network

Description

Usage

Arguments

Format