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java.lang.Objectorg.apache.commons.math3.stat.correlation.PearsonsCorrelation
public class PearsonsCorrelation
Computes Pearson's product-moment correlation coefficients for pairs of arrays or columns of a matrix.
The constructors that take RealMatrix
or
double[][]
arguments generate correlation matrices. The
columns of the input matrices are assumed to represent variable values.
Correlations are given by the formula
cor(X, Y) = Σ[(xi - E(X))(yi - E(Y))] / [(n - 1)s(X)s(Y)]
where E(X)
is the mean of X
, E(Y)
is the mean of the Y
values and s(X), s(Y) are standard deviations.
Constructor Summary | |
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PearsonsCorrelation()
Create a PearsonsCorrelation instance without data |
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PearsonsCorrelation(Covariance covariance)
Create a PearsonsCorrelation from a Covariance . |
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PearsonsCorrelation(double[][] data)
Create a PearsonsCorrelation from a rectangular array whose columns represent values of variables to be correlated. |
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PearsonsCorrelation(RealMatrix matrix)
Create a PearsonsCorrelation from a RealMatrix whose columns represent variables to be correlated. |
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PearsonsCorrelation(RealMatrix covarianceMatrix,
int numberOfObservations)
Create a PearsonsCorrelation from a covariance matrix. |
Method Summary | |
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RealMatrix |
computeCorrelationMatrix(double[][] data)
Computes the correlation matrix for the columns of the input rectangular array. |
RealMatrix |
computeCorrelationMatrix(RealMatrix matrix)
Computes the correlation matrix for the columns of the input matrix. |
double |
correlation(double[] xArray,
double[] yArray)
Computes the Pearson's product-moment correlation coefficient between the two arrays. |
RealMatrix |
covarianceToCorrelation(RealMatrix covarianceMatrix)
Derives a correlation matrix from a covariance matrix. |
RealMatrix |
getCorrelationMatrix()
Returns the correlation matrix |
RealMatrix |
getCorrelationPValues()
Returns a matrix of p-values associated with the (two-sided) null hypothesis that the corresponding correlation coefficient is zero. |
RealMatrix |
getCorrelationStandardErrors()
Returns a matrix of standard errors associated with the estimates in the correlation matrix. getCorrelationStandardErrors().getEntry(i,j) is the standard
error associated with getCorrelationMatrix.getEntry(i,j) |
Methods inherited from class java.lang.Object |
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clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
Constructor Detail |
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public PearsonsCorrelation()
public PearsonsCorrelation(double[][] data)
data
- rectangular array with columns representing variables
IllegalArgumentException
- if the input data array is not
rectangular with at least two rows and two columns.public PearsonsCorrelation(RealMatrix matrix)
matrix
- matrix with columns representing variables to correlatepublic PearsonsCorrelation(Covariance covariance)
Covariance
. The correlation
matrix is computed by scaling the Covariance's covariance matrix.
The Covariance instance must have been created from a data matrix with
columns representing variable values.
covariance
- Covariance instancepublic PearsonsCorrelation(RealMatrix covarianceMatrix, int numberOfObservations)
covarianceMatrix
- covariance matrixnumberOfObservations
- the number of observations in the dataset used to compute
the covariance matrixMethod Detail |
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public RealMatrix getCorrelationMatrix()
public RealMatrix getCorrelationStandardErrors()
getCorrelationStandardErrors().getEntry(i,j)
is the standard
error associated with getCorrelationMatrix.getEntry(i,j)
The formula used to compute the standard error is
SEr = ((1 - r2) / (n - 2))1/2
where r
is the estimated correlation coefficient and
n
is the number of observations in the source dataset.
public RealMatrix getCorrelationPValues()
getCorrelationPValues().getEntry(i,j)
is the probability
that a random variable distributed as tn-2
takes
a value with absolute value greater than or equal to
|r|((n - 2) / (1 - r2))1/2
The values in the matrix are sometimes referred to as the significance of the corresponding correlation coefficients.
MaxCountExceededException
- if an error occurs estimating probabilitiespublic RealMatrix computeCorrelationMatrix(RealMatrix matrix)
matrix
- matrix with columns representing variables to correlate
public RealMatrix computeCorrelationMatrix(double[][] data)
data
- matrix with columns representing variables to correlate
public double correlation(double[] xArray, double[] yArray)
xArray
- first data arrayyArray
- second data array
DimensionMismatchException
- if the arrays lengths do not match
MathIllegalArgumentException
- if there is insufficient datapublic RealMatrix covarianceToCorrelation(RealMatrix covarianceMatrix)
Uses the formula
r(X,Y) = cov(X,Y)/s(X)s(Y)
where
r(·,·)
is the correlation coefficient and
s(·)
means standard deviation.
covarianceMatrix
- the covariance matrix
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