Package edu.cmu.tetrad.search

Class Lofs

java.lang.Object
edu.cmu.tetrad.search.Lofs
public class Lofs extends Object
Implements a number of methods which take a fixed graph as input and use linear, non-Gaussian methods to orient the edges in the graph. where the acronym stands for linear, non-Gaussian Orientation with a Fixed graph Structure (LOFS). The options for different types of scores are given in the enum Lofs.Score. The options for rules to use to do the orientations are given in the enum, Lofs.Rule. Most of these are taken from the literature and can be googled, though we should certainly give this reference for several of them, to which we are indebted:

Hyvärinen, A., & Smith, S. M. (2013). Pairwise likelihood ratios for estimation of non-Gaussian structural equation models. The Journal of Machine Learning Research, 14(1), 111-152.

This class is configured to respect knowledge of forbidden and required edges, including knowledge of temporal tiers.

Version:
$Id: $Id
Author:
josephramsey
See Also:

  • Nested Class Summary

    Nested Classes
    Modifier and Type
    Class
    Description
    static enum 
    Lofs.Rule
    Give a list of options for rules for doing the non-Gaussian orientations.
    static enum 
    Lofs.Score
    Gives a list of options for non-Gaussian transformations that can be used for some scores.

  • Constructor Summary

    Constructors
    Constructor
    Description
    Lofs(Graph graph, List<DataSet> dataSets)
    Constructor.

  • Method Summary

    Modifier and Type
    Method
    Description
    double
    getPValue(double fisherZ)
    Calculates the p-value using Fisher's exact test.
    double
    kernel(double z)
    Calculates the kernel value for a given input.
    double
    kernel1(double z)
    Computes the value of the kernel function 1 for a given input.
    double
    kernel2(double z)
    Calculates the value of the kernel2 function for the given input.
    double
    kernel3(double z)
    This method calculates the value of the kernel function, kernel3, for a given input.
    double
    kernel4(double z)
    Calculates the result of kernel4 function.
    double
    kernel5(double z)
    Calculates the value of the kernel function, kernel5, for the given input.
    double
    kernel6(double z)
    Calculates the value of the kernel function 6 given a parameter z.
    double
    kernel7(double z)
    Computes the value of the kernel7 function for the given value.
    double
    kernel8(double z)
    Calculates the value of the kernel8 function for the given input.
    Graph
    orient()
    Orients the graph and returns the oriented graph.
    double
    scoreRow(int rowIndex, Matrix data, List<List<Integer>> rows, List<List<Double>> parameters)
    Calculates the score for a given row in a matrix using the specified parameters.
    void
    setAlpha(double alpha)
    Sets the alpha to use, where applicable.
    void
    setEpsilon(double epsilon)
    Sets the epsilon value.
    void
    setKnowledge(Knowledge knowledge)
    Sets the knowledge for the object.
    void
    setOrientStrongerDirection(boolean orientStrongerDirection)
    Sets whether orientation should be done in the stronger direction, where applicable.
    void
    setR2Orient2Cycles(boolean r2Orient2Cycles)
    Sets for R2 whether cycles should be oriented.
    void
    setRule(Lofs.Rule rule)
    Sets the rule to use to do the orientation.
    void
    setScore(Lofs.Score score)
    Sets the (LoFS) score to use.
    void
    setSelfLoopStrength(double selfLoopStrength)
    Sets the self-loop strength, if applicable.

    Methods inherited from class java.lang.Object

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

  • Constructor Details

    • Lofs

      public Lofs(Graph graph, List<DataSet> dataSets) throws IllegalArgumentException
      Constructor.
      Parameters:
      graph - The graph to be oriented. Orientations for the graph will be overwritten.
      dataSets - A list of datasets to use to do the orientation. This may be just one dataset. If more than one dataset are given, the data will be concatenated (pooled).
      Throws:
      IllegalArgumentException - if any.

  • Method Details

    • orient

      public Graph orient()
      Orients the graph and returns the oriented graph.
      Returns:
      The oriented graph.

    • setRule

      public void setRule(Lofs.Rule rule)
      Sets the rule to use to do the orientation.
      Parameters:
      rule - This rule.
      See Also:

    • setScore

      public void setScore(Lofs.Score score)
      Sets the (LoFS) score to use.
      Parameters:
      score - This score.
      See Also:

    • setSelfLoopStrength

      public void setSelfLoopStrength(double selfLoopStrength)
      Sets the self-loop strength, if applicable.
      Parameters:
      selfLoopStrength - This strength.

    • setAlpha

      public void setAlpha(double alpha)
      Sets the alpha to use, where applicable.
      Parameters:
      alpha - This alpha.

    • setOrientStrongerDirection

      public void setOrientStrongerDirection(boolean orientStrongerDirection)
      Sets whether orientation should be done in the stronger direction, where applicable.
      Parameters:
      orientStrongerDirection - True, if so.

    • setR2Orient2Cycles

      public void setR2Orient2Cycles(boolean r2Orient2Cycles)
      Sets for R2 whether cycles should be oriented.
      Parameters:
      r2Orient2Cycles - True, if so.

    • scoreRow

      public double scoreRow(int rowIndex, Matrix data, List<List<Integer>> rows, List<List<Double>> parameters)
      Calculates the score for a given row in a matrix using the specified parameters.
      Parameters:
      rowIndex - the index of the row to score
      data - the matrix containing the data
      rows - the list of rows containing the column indices to score
      parameters - the list of parameters for each column index in the rows
      Returns:
      the score of the row

    • setEpsilon

      public void setEpsilon(double epsilon)
      Sets the epsilon value.
      Parameters:
      epsilon - the new value of epsilon

    • setKnowledge

      public void setKnowledge(Knowledge knowledge)
      Sets the knowledge for the object.
      Parameters:
      knowledge - the knowledge to set.
      Throws:
      NullPointerException - if the knowledge is null.

    • getPValue

      public double getPValue(double fisherZ)
      Calculates the p-value using Fisher's exact test. The p-value is the probability of observing a test statistic as extreme as the observed value under the null hypothesis. It is used to determine the statistical significance of the observed value.
      Parameters:
      fisherZ - the Fisher's Z value
      Returns:
      the p-value

    • kernel

      public double kernel(double z)
      Calculates the kernel value for a given input.
      Parameters:
      z - the input value to calculate the kernel value for.
      Returns:
      the calculated kernel value for the given input.

    • kernel1

      public double kernel1(double z)
      Computes the value of the kernel function 1 for a given input. (Gaussian.)
      Parameters:
      z - the input value for which the kernel function is computed
      Returns:
      the value of the kernel function computed for the given input value

    • kernel2

      public double kernel2(double z)
      Calculates the value of the kernel2 function for the given input. (Uniform.)
      Parameters:
      z - the input value to calculate the kernel2 for
      Returns:
      the calculated value of kernel2

    • kernel3

      public double kernel3(double z)
      This method calculates the value of the kernel function, kernel3, for a given input. (Triangular.)
      Parameters:
      z - the input value for which the kernel function is to be calculated
      Returns:
      the calculated value of the kernel function

    • kernel4

      public double kernel4(double z)
      Calculates the result of kernel4 function. (Epanechnikov)
      Parameters:
      z - a double value representing the input parameter
      Returns:
      the result of kernel4 function

    • kernel5

      public double kernel5(double z)
      Calculates the value of the kernel function, kernel5, for the given input. (Quartic)

      The kernel function calculates the value based on the input value z. If the absolute value of z is greater than 1, the function returns 0. Otherwise, it returns the result of the calculation: (15 / 16)

      Parameters:
      z - the input parameter
      Returns:
      the result of kernel5 function

    • kernel6

      public double kernel6(double z)
      Calculates the value of the kernel function 6 given a parameter z. (Triweight)
      Parameters:
      z - the input parameter
      Returns:
      the calculated value of the kernel function 6

    • kernel7

      public double kernel7(double z)
      Computes the value of the kernel7 function for the given value. (Tricube)
      Parameters:
      z - the input value
      Returns:
      the computed value of the kernel7 function

    • kernel8

      public double kernel8(double z)
      Calculates the value of the kernel8 function for the given input. (Cosine)
      Parameters:
      z - the input value for the kernel8 function
      Returns:
      the calculated value of the kernel8 function