dpsdPosLogLike

Number of studied-item conditions.

Number of items in studied condition.

Vector of responses, ranging from 0:(K-1).

cond

Vector of new-studied condition index; 0=new, 1=studied.

Scond

Vector of subject index, starting at 0 with no missing
 subject numbers.

Vector of item index, starting at 0 with no missing
 item numbers.

item

Block of parameters for new-item means.

blockN

Block of parameters for dprime means.

blockD

Block of parameters for recollection values.

blockR

VECTOR of criteria including -Inf and Inf for top and bottom
critieria, respectively. Vector contains the (K+1) criteria for the
first subjects, followed by those for the second subject, etc.

crit

Computes log likelihood for DPSD model with positive d'

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

dpsdPosLogLike function

<dl><dt>R</dt>
<dd>Total number of trials.</dd><dt>NN</dt>
<dd>Number of new-item conditions.</dd><dt>NS</dt>
<dd>Number of studied-item conditions.</dd><dt>I</dt>
<dd>Number of subjects.</dd><dt>JN</dt>
<dd>Number of items in new condition.</dd><dt>JS</dt>
<dd>Number of items in studied condition.</dd><dt>K</dt>
<dd>Number of response options.</dd><dt>dat</dt>
<dd>Vector of responses, ranging from 0:(K-1).</dd><dt>cond</dt>
<dd>Vector of condition index.</dd><dt>Scond</dt>
<dd>Vector of new-studied condition index; 0=new, 1=studied.</dd><dt>sub</dt>
<dd>Vector of subject index, starting at 0 with no missing
 subject numbers.</dd><dt>item</dt>
<dd>Vector of item index, starting at 0 with no missing
 item numbers.</dd><dt>lag</dt>
<dd>Vector of lag index.</dd><dt>blockN</dt>
<dd>Block of parameters for new-item means.</dd><dt>blockD</dt>
<dd>Block of parameters for dprime means.</dd><dt>blockR</dt>
<dd>Block of parameters for recollection values.</dd><dt>crit</dt>
<dd>VECTOR of criteria including -Inf and Inf for top and bottom
critieria, respectively. Vector contains the (K+1) criteria for the
first subjects, followed by those for the second subject, etc.</dd></dl>

Arguments

function dpsdPosLogLike — dpsdPosLogLike

<dl>

<dt>R</dt>
<dd>Total number of trials.</dd>

<dt>NN</dt>
<dd>Number of new-item conditions.</dd>

<dt>NS</dt>
<dd>Number of studied-item conditions.</dd>

<dt>I</dt>
<dd>Number of subjects.</dd>

<dt>JN</dt>
<dd>Number of items in new condition.</dd>

<dt>JS</dt>
<dd>Number of items in studied condition.</dd>

<dt>K</dt>
<dd>Number of response options.</dd>

<dt>dat</dt>
<dd>Vector of responses, ranging from 0:(K-1).</dd>

<dt>cond</dt>
<dd>Vector of condition index.</dd>

<dt>Scond</dt>
<dd>Vector of new-studied condition index; 0=new, 1=studied.</dd>

<dt>sub</dt>
<dd>Vector of subject index, starting at 0 with no missing
 subject numbers.</dd>

<dt>item</dt>
<dd>Vector of item index, starting at 0 with no missing
 item numbers.</dd>

<dt>lag</dt>
<dd>Vector of lag index.</dd>

<dt>blockN</dt>
<dd>Block of parameters for new-item means.</dd>

<dt>blockD</dt>
<dd>Block of parameters for dprime means.</dd>

<dt>blockR</dt>
<dd>Block of parameters for recollection values.</dd>

<dt>crit</dt>
<dd>VECTOR of criteria including -Inf and Inf for top and bottom
critieria, respectively. Vector contains the (K+1) criteria for the
first subjects, followed by those for the second subject, etc.</dd>

</dl>

dpsdPosLogLike: function dpsdPosLogLike

Description

Usage

Arguments