public class OneWayAnova extends Object
Tests for differences between two or more categories of univariate data
(for example, the body mass index of accountants, lawyers, doctors and
computer programmers). When two categories are given, this is equivalent to
the TTest
.
Uses the Hipparchus F Distribution implementation
to estimate exact p-values.
This implementation is based on a description at http://faculty.vassar.edu/lowry/ch13pt1.html
Abbreviations: bg = between groups, wg = within groups, ss = sum squared deviations
Constructor | Description |
---|---|
OneWayAnova() |
Default constructor.
|
Modifier and Type | Method | Description |
---|---|---|
double |
anovaFValue(Collection<double[]> categoryData) |
Computes the ANOVA F-value for a collection of
double[]
arrays. |
double |
anovaPValue(Collection<double[]> categoryData) |
Computes the ANOVA P-value for a collection of
double[]
arrays. |
double |
anovaPValue(Collection<StreamingStatistics> categoryData,
boolean allowOneElementData) |
Computes the ANOVA P-value for a collection of
StreamingStatistics . |
boolean |
anovaTest(Collection<double[]> categoryData,
double alpha) |
Performs an ANOVA test, evaluating the null hypothesis that there
is no difference among the means of the data categories.
|
public double anovaFValue(Collection<double[]> categoryData) throws MathIllegalArgumentException, NullArgumentException
double[]
arrays.
Preconditions:
Collection
must contain
double[]
arrays.double[]
arrays in the
categoryData
collection and each of these arrays must
contain at least two values.This implementation computes the F statistic using the definitional formula
F = msbg/mswgwhere
msbg = between group mean square mswg = within group mean squareare as defined here
categoryData
- Collection
of double[]
arrays each containing data for one categoryNullArgumentException
- if categoryData
is null
MathIllegalArgumentException
- if the length of the categoryData
array is less than 2 or a contained double[]
array does not have
at least two valuespublic double anovaPValue(Collection<double[]> categoryData) throws MathIllegalArgumentException, NullArgumentException, MathIllegalStateException
double[]
arrays.
Preconditions:
Collection
must contain
double[]
arrays.double[]
arrays in the
categoryData
collection and each of these arrays must
contain at least two values.
This implementation uses the
Hipparchus F Distribution implementation
to estimate the exact
p-value, using the formula
p = 1 - cumulativeProbability(F)where
F
is the F value and cumulativeProbability
is the Hipparchus implementation of the F distribution.categoryData
- Collection
of double[]
arrays each containing data for one categoryNullArgumentException
- if categoryData
is null
MathIllegalArgumentException
- if the length of the categoryData
array is less than 2 or a contained double[]
array does not have
at least two valuesMathIllegalStateException
- if the p-value can not be computed due to a convergence errorMathIllegalStateException
- if the maximum number of iterations is exceededpublic double anovaPValue(Collection<StreamingStatistics> categoryData, boolean allowOneElementData) throws MathIllegalArgumentException, NullArgumentException, MathIllegalStateException
StreamingStatistics
.
Preconditions:
Collection
must contain
StreamingStatistics
.StreamingStatistics
in the
categoryData
collection and each of these statistics must
contain at least two values.
This implementation uses the
Hipparchus F Distribution implementation
to estimate the exact
p-value, using the formula
p = 1 - cumulativeProbability(F)where
F
is the F value and cumulativeProbability
is the Hipparchus implementation of the F distribution.categoryData
- Collection
of StreamingStatistics
each containing data for one categoryallowOneElementData
- if true, allow computation for one catagory
only or for one data element per categoryNullArgumentException
- if categoryData
is null
MathIllegalArgumentException
- if the length of the categoryData
array is less than 2 or a contained StreamingStatistics
does not have
at least two valuesMathIllegalStateException
- if the p-value can not be computed due to a convergence errorMathIllegalStateException
- if the maximum number of iterations is exceededpublic boolean anovaTest(Collection<double[]> categoryData, double alpha) throws MathIllegalArgumentException, NullArgumentException, MathIllegalStateException
Preconditions:
Collection
must contain
double[]
arrays.double[]
arrays in the
categoryData
collection and each of these arrays must
contain at least two values.
This implementation uses the
Hipparchus F Distribution implementation
to estimate the exact
p-value, using the formula
p = 1 - cumulativeProbability(F)where
F
is the F value and cumulativeProbability
is the Hipparchus implementation of the F distribution.
True is returned iff the estimated p-value is less than alpha.
categoryData
- Collection
of double[]
arrays each containing data for one categoryalpha
- significance level of the testNullArgumentException
- if categoryData
is null
MathIllegalArgumentException
- if the length of the categoryData
array is less than 2 or a contained double[]
array does not have
at least two valuesMathIllegalArgumentException
- if alpha
is not in the range (0, 0.5]MathIllegalStateException
- if the p-value can not be computed due to a convergence errorMathIllegalStateException
- if the maximum number of iterations is exceededCopyright © 2016–2018 Hipparchus.org. All rights reserved.