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java.lang.Objectorg.statcato.statistics.inferential.MultipleRegression2
public class MultipleRegression2
Multiple regression for non-linear models. Variations (explained, unexplained, total) are calculated using matrix operations.
Constructor Summary | |
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MultipleRegression2(java.util.Vector<java.util.Vector<java.lang.Double>> IndependentVars,
java.util.Vector<java.lang.Double> DependentVar,
boolean hasConstant)
Constructor. |
Method Summary | |
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double |
AdjustedCoefficientOfDetermination()
Returns the adjusted coefficient of determination. |
double |
CoefficientOfDetermination()
Returns the coefficient of determination r^2, the amount of the variation in y that is explained by the regression line. |
double |
ExplainedVariation()
Returns the explained variation (SSR, the sum of squared differences between the predicted y value and the average y value). |
int |
NumIndepVar()
Returns the number of independent variables. |
double |
PValue()
Returns the p-Value of test statistics. |
Jama.Matrix |
RegressionEqCoefficients()
Returns the coefficients of the regression equation y = b_0 + b_1 * x_1 + ... |
int |
SampleSize()
Returns the sample size. |
double |
StandardError()
Returns the standard error of estimate, sqrt(unexplained variation / (n-2)). |
double |
TestStatistics()
Returns the test statistics F. |
java.lang.String |
toString()
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double |
TotalVariation()
Returns the total variation (SST, the sum of squared differences between the y values and the average y value). |
double |
UnexplainedVariation()
Returns the unexplained variation (the sum of squared differences between the predicted y value and the y value). |
Jama.Matrix |
XVar(int i)
Returns the i th value of all the independent variables as a 1 by k matrix. |
double |
YPredicted(Jama.Matrix var)
Returns the predicted y value given a vector of values of the independent variables using the regression equation. |
Methods inherited from class java.lang.Object |
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clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait |
Constructor Detail |
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public MultipleRegression2(java.util.Vector<java.util.Vector<java.lang.Double>> IndependentVars, java.util.Vector<java.lang.Double> DependentVar, boolean hasConstant)
IndependentVars
- a vector of vectors of double, where each
vector is an independent variable with the same number of valuesDependentVar
- a vector of double, which has the same number of
values as the independent variablesMethod Detail |
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public Jama.Matrix RegressionEqCoefficients()
public double YPredicted(Jama.Matrix var)
var
- a vector of double that has the same number of values as
the number of independent variables.
public double TotalVariation()
public Jama.Matrix XVar(int i)
i
- index
public double ExplainedVariation()
public double UnexplainedVariation()
public double CoefficientOfDetermination()
public double AdjustedCoefficientOfDetermination()
public double StandardError()
public double TestStatistics()
public double PValue()
public int SampleSize()
public int NumIndepVar()
public java.lang.String toString()
toString
in class java.lang.Object
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