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pcalg (version 1.1-6)

Estimation of CPDAG/PAG and causal inference using the IDA algorithm

Description

Standard and robust estimation of the equivalence class of a Directed Acyclic Graph (DAG) via the PC-Algorithm. The equivalence class is represented by its (unique) Completete Partially Directed Acyclic Graph (CPDAG). Furthermore, a PAG instead of a CPDAG can be estimated if latent variables and/or selection variables are assumed to be present. FCI and RFCI are available for estimating PAGs. Functions for causal inference using the IDA algorithm (based on do-calculus of Judea Pearl) are provided for CPDAGs.

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Version

Install

install.packages('pcalg')

Monthly Downloads

1,818

Version

1.1-6

License

GPL (>= 2)

Maintainer

Markus Kalisch

Last Published

March 22nd, 2013

Functions in pcalg (1.1-6)

Test for (conditional) independence for binary data

Compute (Large) Correlation Matrix

Generate Multivariate Data according to a DAG

Estimate the equivalence class of a MAG (PAG) using the FCI Algorithm

Iteration through a list of all combinations of choose(n,k)

Extend a Partially Directed Acyclic Graph (PDAG) to a DAG

Estimate the equivalence class of a DAG using the PC algorithm

Compute set of intervention effects

Latent Variable Graphical Model Data Example

Estimate the equivalence class of a MAG (PAG) using the RFCI Algorithm

Generate a Directed Acyclic Graph (DAG) randomly

Compute possible d-sep of node x

Graphical Model Discrete 5-Dim Example Data

Compute Partial Correlations

pcSelect.presel

Estimate Subgraph around a Response Variable using Preselection

Test for (conditional) independence for gaussian data

Extend a pcAlgo-object containing a skeleton to a PDAG

Test for (conditional) independence for discrete data

Computing the correlation graph

Convert a DAG to a CPDAG

Class "fciAlgo"

PC-Select: Estimate subgraph around a response variable

G square Test for (Conditional) Independence of Discrete Data

Internal function for conservative PC algorithm

Graphical Model 8-Dimensional Gaussian Example Data

Extend a pcAlgo-object containing a skeleton to a PAG

Conditional Independence by Fisher's Z-Transformation

Estimate the skeleton of a DAG using the PC Algorithm

Compute Structural Hamming Distance (SHD)

PC-Algorithm: Estimate the Underlying Graph (Skeleton) or Equivalence Class (CPDAG) of a DAG

Plot the subgraph around a Specific Node in a Graph Object

udag2pdagSpecial

Extend a pcAlgo-object containing a skeleton to a PDAG using different methods if problems occur

Graphical Model 5-Dim Binary Example Data

udag2pdagRelaxed

Extend a pcAlgo-object containing a skeleton to a PDAG

beta.special.pcObj

Compute set of intervention effects in a fast way

Graphical Model IDA Data Example

Estimate Multiset of Possible Total Causal Effects

Compute Possible-D-Sep for Each Node and Adapt Graph Accordingly

Compare two graphs in terms of TPR, FPR and TDR

Multiset of Possible Total Causal Effects for Several Target Var.s

G square Test for (Conditional) Independence of Binary Data

Test for d-separation in a DAG

Plot partial ancestral graphs (PAG)

Test for d-separation in a DAG

Internal Pcalg Functions