com.imsl.stat
Class SelectionRegression.Statistics

java.lang.Object
  com.imsl.stat.SelectionRegression.Statistics

All Implemented Interfaces:

Serializable

Enclosing class:

SelectionRegression

public class SelectionRegression.Statistics
extends Object
implements Serializable

Statistics contains statistics related to the regression coefficients.

See Also:

Serialized Form

Method Summary

double[][]	getCoefficientStatistics(int regressionIndex) Returns the coefficients statistics for each of the best regressions found for each subset considered.
double[]	getCriterionValues(int numVariables) Returns an array containing the values of the best criterion for the number of variables considered.
int[][]	getIndependentVariables(int numVariables) Returns the identification numbers for the independent variables for the number of variables considered and in the same order as the criteria returned by getCriterionValues(int).

Methods inherited from class java.lang.Object

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

Method Detail

getCoefficientStatistics

public double[][] getCoefficientStatistics(int regressionIndex)

Returns the coefficients statistics for each of the best regressions found for each subset considered.

The value set by method SelectionRegression.setMaximumBestFound(int) determines the total number of best regressions to find. The number of best regression is equal to (maxSubset x maxFound), if criterion R_SQUARED_CRITERION is specified or it is equal to maxFound if either MALLOWS_CP_CRITERION or ADJUSTED_R_SQUARED_CRITERION is specified.

Each row contains statistics related to the regression coefficients of the best models. The regressions are ordered so that the better regressions appear first. The statistic in the columns are as follows (inferences are conditional on the selected model):

Column	Description
0	variable number
1	coefficient estimate
2	estimated standard error of the estimate
3	t-statistic for the test that the coefficient is 0
4	p-value for the two-sided t test

Parameters:

regressionIndex - An int which specifies the index of the best regression statistics to return. There will be 0 to (maxSubset x maxFound - 1) best regressions if R_SQUARED_CRITERION is specified or 0 to (maxFound - 1) if either MALLOWS_CP_CRITERION or ADJUSTED_R_SQUARED_CRITERION is specified.

Returns:

A two-dimensional double array containing the regression statistics.

See Also:

SelectionRegression.R_SQUARED_CRITERION, SelectionRegression.ADJUSTED_R_SQUARED_CRITERION, SelectionRegression.MALLOWS_CP_CRITERION

getCriterionValues

public double[] getCriterionValues(int numVariables)

Returns an array containing the values of the best criterion for the number of variables considered.

Parameters:

numVariables - An int which specifies the number of variables considered.

Returns:

A double array with maxSubset rows and nCandidate columns containing the criterion values.

getIndependentVariables

public int[][] getIndependentVariables(int numVariables)

Returns the identification numbers for the independent variables for the number of variables considered and in the same order as the criteria returned by getCriterionValues(int).

Parameters:

numVariables - An int which specifies the number of variables considered.

Returns:

An int matrix containing the identification numbers for the independent variables considered.