public class KolmogorovOneSample extends Object implements Serializable
KolmogorovOneSample
performs a Kolmogorov-Smirnov
goodness-of-fit test in one sample.
The hypotheses tested follow:
The theoretical CDF is assumed to be continuous.
If the CDF is not continuous,
the statistics will not be computed correctly.
Estimation of parameters in the theoretical CDF from the sample data will tend to make the p-values associated with the test statistics too liberal. The empirical CDF will tend to be closer to the theoretical CDF than it should be.
No attempt is made to check that all points in the sample are in the support of the theoretical CDF. If all sample points are not in the support of the CDF, the null hypothesis must be rejected.
Constructor and Description |
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KolmogorovOneSample(CdfFunction cdf,
double[] x)
Constructs a one sample Kolmogorov-Smirnov goodness-of-fit test.
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Modifier and Type | Method and Description |
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double |
getMaximumDifference()
Returns
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double |
getMinimumDifference()
Returns
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int |
getNumberMissing()
Returns the number of missing values in the data.
|
int |
getNumberOfTies()
Returns the number of ties in the data.
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double |
getOneSidedPValue()
Probability of the statistic exceeding D under
the null hypothesis of equality and against the
one-sided alternative.
|
double |
getTestStatistic()
Returns
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double |
getTwoSidedPValue()
Probability of the statistic exceeding D under
the null hypothesis of equality and against the
two-sided alternative.
|
double |
getZ()
Returns the normalized D statistic without the continuity correction applied.
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public KolmogorovOneSample(CdfFunction cdf, double[] x)
cdf
- is the cdf function, x
- is a double
array containing the observations.public double getMaximumDifference()
public double getMinimumDifference()
public int getNumberMissing()
public int getNumberOfTies()
public double getOneSidedPValue()
public double getTestStatistic()
public double getTwoSidedPValue()
getOneSidedPValue
,
(or 1.0 if public double getZ()
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Built October 13 2015.