pc_effect

Creates a pattern causality effect object that contains information about
the received and exerted influences for different causality types.
This function constructs an object of class <code>pc_effect</code> to store the results
of effect analysis.

A comprehensive package for detecting and analyzing causal relationships in complex systems using pattern-based approaches. Key features include state space reconstruction, pattern identification, and causality strength evaluation.

Hui Wang

patterncausality

Pattern Causality Algorithm

Stavros Stavroglou

Athanasios Pantelous

pc_effect function

<dl><dt>positive</dt>
<dd>Data frame containing positive causality effects.</dd>
<dt>negative</dt>
<dd>Data frame containing negative causality effects.</dd>
<dt>dark</dt>
<dd>Data frame containing dark causality effects.</dd>
<dt>items</dt>
<dd>Names of items in the analysis.</dd></dl>

Arguments

Pattern Causality Effect Object — pc_effect

<dl>

<dt>positive</dt>
<dd>Data frame containing positive causality effects.</dd>


<dt>negative</dt>
<dd>Data frame containing negative causality effects.</dd>


<dt>dark</dt>
<dd>Data frame containing dark causality effects.</dd>


<dt>items</dt>
<dd>Names of items in the analysis.</dd>

</dl>

pc_effect: Pattern Causality Effect Object

Description

Usage

Value

Arguments