tpc_example

A small simulated data example intended to showcase the TPC algorithm. Note that the variable name
prefixes defines which period they are related to ("child", "youth" or "oldage").

datasets

Tools for causal structure learning from observational data, with emphasis on temporally ordered variables.
The package implements the Temporal Peter–Clark (TPC) algorithm (Petersen, Osler & Ekstrøm, 2021;
<doi:10.1093/aje/kwab087>), the Temporal Greedy Equivalence Search (TGES) algorithm (Larsen, Ekstrøm & Petersen,
2025; <doi:10.48550/arXiv.2502.06232>) and Temporal Fast Causal Inference (TFCI).
It provides a unified framework for specifying background knowledge,
which can be incorporated into the implemented algorithms from the R packages 'bnlearn' (Scutari, 2010;
<doi:10.18637/jss.v035.i03>) and
'pcalg' (Kalish et al., 2012; <doi:10.18637/jss.v047.i11>), as well as the Java library 'Tetrad'
(Scheines et al., 1998; <doi:10.1207/s15327906mbr3301_3>).
The package further includes utilities for visualization, comparison, and evaluation of graph structures,
facilitating performance evaluation and methodological studies.

Bjarke Hautop Kristensen

causalDisco

Tools for Causal Discovery on Observational Data

Frederik Fabricius-Bjerre

Anne Helby Petersen

Claus Thorn Ekstrøm

Tobias Ellegaard Larsen

tpc_example function

A data.frame with 200 rows and 6 variables.<dl>
<dt>child_x1</dt>
<dd>Structural equation: \(X_1 := \epsilon_1\) with \(\epsilon_1 \sim \mathrm{Unif}\{0,1\}\)</dd><dt>child_x2</dt>
<dd>Structural equation: \(X_2 := 2 \cdot X_1 + \epsilon_2\) with \(\epsilon_2 \sim N(0,1)\)</dd><dt>youth_x3</dt>
<dd>Structural equation: \(X_3 := \epsilon_3\) with \(\epsilon_3 \sim \mathrm{Unif}\{0, 1\}\)</dd><dt>youth_x4</dt>
<dd>Structural equation: \(X_4 := X_2 + \epsilon_4\) with \(\epsilon_4 \sim N(0,1)\)</dd><dt>oldage_x5</dt>
<dd>Structural equation: \(X_5 := X_3^2 + X_3 - 3 \cdot X_2 + \epsilon_5\) with \(\epsilon_5 \sim N(0,1)\)</dd><dt>oldage_x6</dt>
<dd>Structural equation: \(X_6 := X_4^3 + X_4^2 + 2 \cdot X_5 + \epsilon_6\) with \(\epsilon_6 \sim N(0,1)\)</dd>
</dl>

Format

Simulated Life-Course Data — tpc_example

A data.frame with 200 rows and 6 variables.<dl>
<dt>child_x1</dt>
<dd>Structural equation: \(X_1 := \epsilon_1\) with \(\epsilon_1 \sim \mathrm{Unif}\{0,1\}\)</dd>

<dt>child_x2</dt>
<dd>Structural equation: \(X_2 := 2 \cdot X_1 + \epsilon_2\) with \(\epsilon_2 \sim N(0,1)\)</dd>

<dt>youth_x3</dt>
<dd>Structural equation: \(X_3 := \epsilon_3\) with \(\epsilon_3 \sim \mathrm{Unif}\{0, 1\}\)</dd>

<dt>youth_x4</dt>
<dd>Structural equation: \(X_4 := X_2 + \epsilon_4\) with \(\epsilon_4 \sim N(0,1)\)</dd>

<dt>oldage_x5</dt>
<dd>Structural equation: \(X_5 := X_3^2 + X_3 - 3 \cdot X_2 + \epsilon_5\) with \(\epsilon_5 \sim N(0,1)\)</dd>

<dt>oldage_x6</dt>
<dd>Structural equation: \(X_6 := X_4^3 + X_4^2 + 2 \cdot X_5 + \epsilon_6\) with \(\epsilon_6 \sim N(0,1)\)</dd>


</dl>

tpc_example: Simulated Life-Course Data

Description

Usage

Arguments

Format

References

Examples