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java.lang.Objectorg.apache.commons.math.stat.inference.ChiSquareTestImpl
Implements Chi-Square test statistics defined in the ChiSquareTest
interface.
Constructor Summary | |
ChiSquareTestImpl()
Construct a ChiSquareTestImpl |
Method Summary | |
double |
chiSquare(double[] expected,
long[] observed)
Computes the Chi-Square statistic comparing observed and expected
freqeuncy counts. |
double |
chiSquare(long[][] counts)
Computes the Chi-Square statistic associated with a chi-square test of independence based on the input counts
array, viewed as a two-way table. |
double |
chiSquareTest(double[] expected,
long[] observed)
Returns the observed significance level, or p-value, associated with a Chi-square goodness of fit test comparing the observed
frequency counts to those in the expected array. |
boolean |
chiSquareTest(double[] expected,
long[] observed,
double alpha)
Performs a Chi-square goodness of fit test evaluating the null hypothesis that the observed counts conform to the frequency distribution described by the expected counts, with significance level alpha . |
double |
chiSquareTest(long[][] counts)
Returns the observed significance level, or p-value, associated with a chi-square test of independence based on the input counts
array, viewed as a two-way table. |
boolean |
chiSquareTest(long[][] counts,
double alpha)
Performs a chi-square test of independence evaluating the null hypothesis that the classifications represented by the counts in the columns of the input 2-way table are independent of the rows, with significance level alpha . |
protected DistributionFactory |
getDistributionFactory()
Gets a DistributionFactory to use in creating ChiSquaredDistribution instances. |
Methods inherited from class java.lang.Object |
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
Constructor Detail |
public ChiSquareTestImpl()
Method Detail |
public double chiSquare(double[] expected, long[] observed) throws IllegalArgumentException
ChiSquareTest
observed
and expected
freqeuncy counts.
This statistic can be used to perform a Chi-Square test evaluating the null hypothesis that the observed counts follow the expected distribution.
Preconditions:
If any of the preconditions are not met, an
IllegalArgumentException
is thrown.
chiSquare
in interface ChiSquareTest
observed
- array of observed frequency countsexpected
- array of expected frequency counts
IllegalArgumentException
- if preconditions are not met
or length is less than 2public double chiSquareTest(double[] expected, long[] observed) throws IllegalArgumentException, MathException
ChiSquareTest
observed
frequency counts to those in the expected
array.
The number returned is the smallest significance level at which one can reject the null hypothesis that the observed counts conform to the frequency distribution described by the expected counts.
Preconditions:
If any of the preconditions are not met, an
IllegalArgumentException
is thrown.
chiSquareTest
in interface ChiSquareTest
observed
- array of observed frequency countsexpected
- array of exptected frequency counts
IllegalArgumentException
- if preconditions are not met
MathException
- if an error occurs computing the p-valuepublic boolean chiSquareTest(double[] expected, long[] observed, double alpha) throws IllegalArgumentException, MathException
ChiSquareTest
alpha
. Returns true iff the null hypothesis can be rejected
with 100 * (1 - alpha) percent confidence.
Example:
To test the hypothesis that observed
follows
expected
at the 99% level, use
chiSquareTest(expected, observed, 0.01)
Preconditions:
0 < alpha < 0.5
If any of the preconditions are not met, an
IllegalArgumentException
is thrown.
chiSquareTest
in interface ChiSquareTest
observed
- array of observed frequency countsexpected
- array of exptected frequency countsalpha
- significance level of the test
IllegalArgumentException
- if preconditions are not met
MathException
- if an error occurs performing the testpublic double chiSquare(long[][] counts) throws IllegalArgumentException
ChiSquareTest
counts
array, viewed as a two-way table.
The rows of the 2-way table are count[0], ... , count[count.length - 1]
Preconditions:
counts
must have at least 2 columns and
at least 2 rows.
If any of the preconditions are not met, an
IllegalArgumentException
is thrown.
chiSquare
in interface ChiSquareTest
counts
- array representation of 2-way table
IllegalArgumentException
- if preconditions are not metpublic double chiSquareTest(long[][] counts) throws IllegalArgumentException, MathException
ChiSquareTest
counts
array, viewed as a two-way table.
The rows of the 2-way table are count[0], ... , count[count.length - 1]
Preconditions:
counts
must have at least 2 columns and
at least 2 rows.
If any of the preconditions are not met, an
IllegalArgumentException
is thrown.
chiSquareTest
in interface ChiSquareTest
counts
- array representation of 2-way table
IllegalArgumentException
- if preconditions are not met
MathException
- if an error occurs computing the p-valuepublic boolean chiSquareTest(long[][] counts, double alpha) throws IllegalArgumentException, MathException
ChiSquareTest
alpha
. Returns true iff the null hypothesis can be rejected
with 100 * (1 - alpha) percent confidence.
The rows of the 2-way table are count[0], ... , count[count.length - 1]
Example:
To test the null hypothesis that the counts in count[0], ... , count[count.length - 1]
all correspond to the same underlying probability distribution at the 99% level, use
chiSquareTest(counts, 0.01)
Preconditions:
counts
must have at least 2 columns and
at least 2 rows.
If any of the preconditions are not met, an
IllegalArgumentException
is thrown.
chiSquareTest
in interface ChiSquareTest
counts
- array representation of 2-way tablealpha
- significance level of the test
IllegalArgumentException
- if preconditions are not met
MathException
- if an error occurs performing the testprotected DistributionFactory getDistributionFactory()
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