dpsdSample2

~~Describe <code>dat</code> here~~

~~Describe <code>keep</code> here~~

keep

~~Describe <code>getDIC</code> here~~

getDIC

~~Describe <code>Hier</code> here~~

Hier

~~Describe <code>jump</code> here~~

jump

This is just a way to sample the DPSD model with no mus (grand means) to
make it easier to fit the models to data with no item effects and
non-hierarchical priors. In short, this should never be used except for
comparison purposes.

internal

Contains functions for fitting hierarchical versions of
EVSD, UVSD, DPSD, DPSD with d' restricted to be positive, and
our gamma signal detection model to recognition memory
confidence-ratings data.

Mike

hbmem

Hierarchical Bayesian Analysis of Recognition Memory

dpsdSample2 function

<dl> <dt>dat</dt>
<dd>~~Describe <code>dat</code> here~~</dd> <dt>M</dt>
<dd>~~Describe <code>M</code> here~~</dd> <dt>keep</dt>
<dd>~~Describe <code>keep</code> here~~</dd> <dt>getDIC</dt>
<dd>~~Describe <code>getDIC</code> here~~</dd> <dt>Hier</dt>
<dd>~~Describe <code>Hier</code> here~~</dd> <dt>jump</dt>
<dd>~~Describe <code>jump</code> here~~</dd></dl>

Arguments

Fit DPSD model with means in participant effect — dpsdSample2

<dl>

 <dt>dat</dt>
<dd>~~Describe <code>dat</code> here~~</dd>

 <dt>M</dt>
<dd>~~Describe <code>M</code> here~~</dd>

 <dt>keep</dt>
<dd>~~Describe <code>keep</code> here~~</dd>

 <dt>getDIC</dt>
<dd>~~Describe <code>getDIC</code> here~~</dd>

 <dt>Hier</dt>
<dd>~~Describe <code>Hier</code> here~~</dd>

 <dt>jump</dt>
<dd>~~Describe <code>jump</code> here~~</dd>

</dl>

dpsdSample2: Fit DPSD model with means in participant effect

Description

Usage

Arguments