Package edu.cmu.tetrad.search

Class Ida

java.lang.Object

edu.cmu.tetrad.search.Ida

public class Ida
extends Object

Implements the IDA algorithm, Maathuis, Marloes H., Markus Kalisch, and Peter Bühlmann. "Estimating high-dimensional intervention effects from observational data." The Annals of Statistics 37.6A (2009): 3133-3164.

Author:

jdramsey@andrew.cmu.edu

Nested Class Summary

Nested Classes

Modifier and Type	Class	Description
static class	Ida.NodeEffects	A list of nodes and corresponding minimum effects.

Constructor Summary

Constructors

Constructor	Description
Ida(DataSet dataSet, Graph pattern, List<Node> possibleCauses)

Method Summary

Modifier and Type	Method	Description
Map<Node,Double>	calculateMinimumEffectsOnY(Node y)	Returns a map from nodes in V \ {Y} to their minimum effects.
double	distance(LinkedList<Double> effects, double trueEffect)
Ida.NodeEffects	getSortedMinEffects(Node y)	Returns the minimum effects of X on Y for X in V \ {Y}, sorted downward by minimum effect
double	trueEffect(Node x, Node y, Graph trueDag)

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Details

Ida

public Ida(DataSet dataSet,
 Graph pattern,
 List<Node> possibleCauses)

Method Details

getSortedMinEffects

public Ida.NodeEffects getSortedMinEffects(Node y)

Returns the minimum effects of X on Y for X in V \ {Y}, sorted downward by minimum effect

Parameters:

y - The child variable.

Returns:

Two sorted lists, one of nodes, the other of corresponding minimum effects, sorted downward by minimum effect size.

trueEffect

public double trueEffect(Node x,
 Node y,
 Graph trueDag)

distance

public double distance(LinkedList<Double> effects,
 double trueEffect)

calculateMinimumEffectsOnY

public Map<Node,Double> calculateMinimumEffectsOnY(Node y)

Returns a map from nodes in V \ {Y} to their minimum effects.

Parameters:

y - The child variable

Returns:

Thia map.