Package edu.cmu.tetrad.regression
Class RegressionResult
java.lang.Object
edu.cmu.tetrad.regression.RegressionResult
- All Implemented Interfaces:
TetradSerializable,Serializable
Stores the various components of a regression result so they can be passed
around together more easily.
- Author:
- Joseph Ramsey
- See Also:
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Constructor Summary
ConstructorsConstructorDescriptionRegressionResult(boolean zeroInterceptAssumed, String[] regressorNames, int n, double[] b, double[] t, double[] p, double[] se, double r2, double rss, double alpha, Vector res) A result for a variety of regression algorithm. -
Method Summary
Modifier and TypeMethodDescriptiondouble[]getCoef()intgetN()intdouble[]getP()doublegetPredictedValue(double[] x) String[]double[]getSe()double[]getT()static RegressionResultGenerates a simple exemplar of this class to test serialization.toString()
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Constructor Details
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RegressionResult
public RegressionResult(boolean zeroInterceptAssumed, String[] regressorNames, int n, double[] b, double[] t, double[] p, double[] se, double r2, double rss, double alpha, Vector res) A result for a variety of regression algorithm.- Parameters:
zeroInterceptAssumed- True iff a zero intercept was assumed in doing the regression, in which case this coefficient is provided; otherwise, not.regressorNames- The list of regressor variable names, in order.n- The sample size.b- The list of coefficients, in order. If a zero intercept was not assumed, this list begins with the intercept.t- The list of t-statistics for the coefficients, in order. If a zero intercept was not assumed, this list begins with the t statistic for the intercept.p- The p-values for the coefficients, in order. If a zero intercept was not assumed, this list begins with the p value for the intercept.se- The standard errors for the coefficients, in order. If a zero intercept was not assumed, this list begins with the standard error of the intercept.r2- The R squared statistic for the regression.rss- The residual sum of squares of the regression.alpha- The alpha value for the regression, determining which regressors are taken to be
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Method Details
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serializableInstance
Generates a simple exemplar of this class to test serialization. -
getN
public int getN()- Returns:
- the number of data points.
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getNumRegressors
public int getNumRegressors()- Returns:
- the number of regressors.
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getCoef
public double[] getCoef()- Returns:
- the array of regression coeffients.
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getT
public double[] getT()- Returns:
- the array of t-statistics for the regression coefficients.
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getP
public double[] getP()- Returns:
- the array of p-values for the regression coefficients.
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getSe
public double[] getSe() -
getRegressorNames
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getPredictedValue
public double getPredictedValue(double[] x) -
toString
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getResultsTable
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getPreamble
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getResiduals
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