fast_history_compute

Computes cumulative history based on common <code>history</code> values and
<code>normalized_tau</code> and <code>mixed_state</code> that are defined for each
random cluster / individual.

Estimates cumulative history for time-series for continuously
viewed bistable perceptual rivalry displays. Computes cumulative history
via a homogeneous first order differential process. I.e., it assumes
exponential growth/decay of the history as a function time and perceptually
dominant state, Pastukhov & Braun (2011) <doi:10.1167/11.10.12>.
Supports Gamma, log normal, and normal distribution families.
Provides a method to compute history directly and example of using the
computation on a custom Stan code.

Alexander (Sasha) Pastukhov

bistablehistory

Cumulative History Analysis for Bistable Perception Time Series

Alexander Pastukhov

fast_history_compute function

<dl><dt>df</dt>
<dd>DataFrame with <code>"state"</code> (integer, 1 and 2 clear state, 3 - mixed state), <code>"duration"</code> (double),
<code>"irandom"</code> (integer, 1-based index of a random cluster), <code>"run_start"</code> (integer, 1 for the first entry of
the run, 0 otherwise), <code>"session_tmean"</code> (double)</dd>
<dt>normalized_tau</dt>
<dd>DoubleVector A normalized tau value for each random cluster / individual. Thus, its length must be
equal to the number of unique indexes in <code>df["irandom"]</code>.</dd>
<dt>mixed_state</dt>
<dd>DoubleVector A values used for the mixed state for each random cluster / individual.
Thus, its length must be equal to the number of unique indexes in <code>df["irandom"]</code>.</dd>
<dt>history_init</dt>
<dd>DoubleVector, size 2. Initial values of history for a run.</dd></dl>

Arguments

Computes cumulative history — fast_history_compute

<dl>

<dt>df</dt>
<dd>DataFrame with <code>"state"</code> (integer, 1 and 2 clear state, 3 - mixed state), <code>"duration"</code> (double),
<code>"irandom"</code> (integer, 1-based index of a random cluster), <code>"run_start"</code> (integer, 1 for the first entry of
the run, 0 otherwise), <code>"session_tmean"</code> (double)</dd>


<dt>normalized_tau</dt>
<dd>DoubleVector A normalized tau value for each random cluster / individual. Thus, its length must be
equal to the number of unique indexes in <code>df["irandom"]</code>.</dd>


<dt>mixed_state</dt>
<dd>DoubleVector A values used for the mixed state for each random cluster / individual.
Thus, its length must be equal to the number of unique indexes in <code>df["irandom"]</code>.</dd>


<dt>history_init</dt>
<dd>DoubleVector, size 2. Initial values of history for a run.</dd>

</dl>

fast_history_compute: Computes cumulative history

Description

Usage

Value

Arguments

Examples