public final class StatUtils extends Object
Modifier and Type | Method and Description |
---|---|
static double |
geometricMean(double... values)
Returns the geometric mean of the entries in the input array, or
Double.NaN if the array is empty. |
static double |
geometricMean(double[] values,
int begin,
int length)
Returns the geometric mean of the entries in the specified portion of
the input array, or
Double.NaN if the designated subarray
is empty. |
static double |
max(double... values)
Returns the maximum of the entries in the input array, or
Double.NaN if the array is empty. |
static double |
max(double[] values,
int begin,
int length)
Returns the maximum of the entries in the specified portion of the input array,
or
Double.NaN if the designated subarray is empty. |
static double |
mean(double... values)
Returns the arithmetic mean of the entries in the input array, or
Double.NaN if the array is empty. |
static double |
mean(double[] values,
int begin,
int length)
Returns the arithmetic mean of the entries in the specified portion of
the input array, or
Double.NaN if the designated subarray
is empty. |
static double |
meanDifference(double[] sample1,
double[] sample2)
Returns the mean of the (signed) differences between corresponding elements of the
input arrays -- i.e., sum(sample1[i] - sample2[i]) / sample1.length.
|
static double |
min(double... values)
Returns the minimum of the entries in the input array, or
Double.NaN if the array is empty. |
static double |
min(double[] values,
int begin,
int length)
Returns the minimum of the entries in the specified portion of the input array,
or
Double.NaN if the designated subarray is empty. |
static double[] |
mode(double... sample)
Returns the sample mode(s).
|
static double[] |
mode(double[] sample,
int begin,
int length)
Returns the sample mode(s).
|
static double[] |
normalize(double... sample)
Normalize (standardize) the sample, so it is has a mean of 0 and a standard deviation of 1.
|
static double |
percentile(double[] values,
double p)
Returns an estimate of the
p th percentile of the values
in the values array. |
static double |
percentile(double[] values,
int begin,
int length,
double p)
Returns an estimate of the
p th percentile of the values
in the values array, starting with the element in (0-based)
position begin in the array and including length
values. |
static double |
populationVariance(double... values)
Returns the
population variance of the entries in the input array, or
Double.NaN if the array is empty. |
static double |
populationVariance(double[] values,
double mean)
Returns the
population variance of the entries in the input array, using the precomputed
mean value.
|
static double |
populationVariance(double[] values,
double mean,
int begin,
int length)
Returns the
population variance of the entries in the specified portion of
the input array, using the precomputed mean value.
|
static double |
populationVariance(double[] values,
int begin,
int length)
Returns the
population variance of the entries in the specified portion of
the input array, or
Double.NaN if the designated subarray
is empty. |
static double |
product(double... values)
Returns the product of the entries in the input array, or
Double.NaN if the array is empty. |
static double |
product(double[] values,
int begin,
int length)
Returns the product of the entries in the specified portion of
the input array, or
Double.NaN if the designated subarray
is empty. |
static double |
sum(double... values)
Returns the sum of the values in the input array, or
Double.NaN if the array is empty. |
static double |
sum(double[] values,
int begin,
int length)
Returns the sum of the entries in the specified portion of
the input array, or
Double.NaN if the designated subarray is empty. |
static double |
sumDifference(double[] sample1,
double[] sample2)
Returns the sum of the (signed) differences between corresponding elements of the
input arrays -- i.e., sum(sample1[i] - sample2[i]).
|
static double |
sumLog(double... values)
Returns the sum of the natural logs of the entries in the input array, or
Double.NaN if the array is empty. |
static double |
sumLog(double[] values,
int begin,
int length)
Returns the sum of the natural logs of the entries in the specified portion of
the input array, or
Double.NaN if the designated subarray is empty. |
static double |
sumSq(double... values)
Returns the sum of the squares of the entries in the input array, or
Double.NaN if the array is empty. |
static double |
sumSq(double[] values,
int begin,
int length)
Returns the sum of the squares of the entries in the specified portion of
the input array, or
Double.NaN if the designated subarray
is empty. |
static double |
variance(double... values)
Returns the variance of the entries in the input array, or
Double.NaN if the array is empty. |
static double |
variance(double[] values,
double mean)
Returns the variance of the entries in the input array, using the
precomputed mean value.
|
static double |
variance(double[] values,
double mean,
int begin,
int length)
Returns the variance of the entries in the specified portion of
the input array, using the precomputed mean value.
|
static double |
variance(double[] values,
int begin,
int length)
Returns the variance of the entries in the specified portion of
the input array, or
Double.NaN if the designated subarray
is empty. |
static double |
varianceDifference(double[] sample1,
double[] sample2,
double meanDifference)
Returns the variance of the (signed) differences between corresponding elements of the
input arrays -- i.e., var(sample1[i] - sample2[i]).
|
public static double sum(double... values) throws MathIllegalArgumentException
Double.NaN
if the array is empty.
Throws IllegalArgumentException
if the input array is null.
values
- array of values to sumDouble.NaN
if the array is emptyMathIllegalArgumentException
- if the array is nullpublic static double sum(double[] values, int begin, int length) throws MathIllegalArgumentException
Double.NaN
if the designated subarray is empty.
Throws IllegalArgumentException
if the array is null.
values
- the input arraybegin
- index of the first array element to includelength
- the number of elements to includeMathIllegalArgumentException
- if the array is null or the array index
parameters are not validpublic static double sumSq(double... values) throws MathIllegalArgumentException
Double.NaN
if the array is empty.
Throws IllegalArgumentException
if the array is null.
values
- input arrayDouble.NaN
if the array is emptyMathIllegalArgumentException
- if the array is nullpublic static double sumSq(double[] values, int begin, int length) throws MathIllegalArgumentException
Double.NaN
if the designated subarray
is empty.
Throws IllegalArgumentException
if the array is null.
values
- the input arraybegin
- index of the first array element to includelength
- the number of elements to includeMathIllegalArgumentException
- if the array is null or the array index
parameters are not validpublic static double product(double... values) throws MathIllegalArgumentException
Double.NaN
if the array is empty.
Throws IllegalArgumentException
if the array is null.
values
- the input arrayMathIllegalArgumentException
- if the array is nullpublic static double product(double[] values, int begin, int length) throws MathIllegalArgumentException
Double.NaN
if the designated subarray
is empty.
Throws IllegalArgumentException
if the array is null.
values
- the input arraybegin
- index of the first array element to includelength
- the number of elements to includeMathIllegalArgumentException
- if the array is null or the array index
parameters are not validpublic static double sumLog(double... values) throws MathIllegalArgumentException
Double.NaN
if the array is empty.
Throws IllegalArgumentException
if the array is null.
See SumOfLogs
.
values
- the input arrayMathIllegalArgumentException
- if the array is nullpublic static double sumLog(double[] values, int begin, int length) throws MathIllegalArgumentException
Double.NaN
if the designated subarray is empty.
Throws IllegalArgumentException
if the array is null.
See SumOfLogs
.
values
- the input arraybegin
- index of the first array element to includelength
- the number of elements to includeMathIllegalArgumentException
- if the array is null or the array index
parameters are not validpublic static double mean(double... values) throws MathIllegalArgumentException
Double.NaN
if the array is empty.
Throws IllegalArgumentException
if the array is null.
See Mean
for
details on the computing algorithm.
values
- the input arrayMathIllegalArgumentException
- if the array is nullpublic static double mean(double[] values, int begin, int length) throws MathIllegalArgumentException
Double.NaN
if the designated subarray
is empty.
Throws IllegalArgumentException
if the array is null.
See Mean
for
details on the computing algorithm.
values
- the input arraybegin
- index of the first array element to includelength
- the number of elements to includeMathIllegalArgumentException
- if the array is null or the array index
parameters are not validpublic static double geometricMean(double... values) throws MathIllegalArgumentException
Double.NaN
if the array is empty.
Throws IllegalArgumentException
if the array is null.
See GeometricMean
for details on the computing algorithm.
values
- the input arrayMathIllegalArgumentException
- if the array is nullpublic static double geometricMean(double[] values, int begin, int length) throws MathIllegalArgumentException
Double.NaN
if the designated subarray
is empty.
Throws IllegalArgumentException
if the array is null.
See GeometricMean
for details on the computing algorithm.
values
- the input arraybegin
- index of the first array element to includelength
- the number of elements to includeMathIllegalArgumentException
- if the array is null or the array index
parameters are not validpublic static double variance(double... values) throws MathIllegalArgumentException
Double.NaN
if the array is empty.
This method returns the bias-corrected sample variance (using n - 1
in
the denominator). Use populationVariance(double[])
for the non-bias-corrected
population variance.
See Variance
for
details on the computing algorithm.
Returns 0 for a single-value (i.e. length = 1) sample.
Throws MathIllegalArgumentException
if the array is null.
values
- the input arrayMathIllegalArgumentException
- if the array is nullpublic static double variance(double[] values, int begin, int length) throws MathIllegalArgumentException
Double.NaN
if the designated subarray
is empty.
This method returns the bias-corrected sample variance (using n - 1
in
the denominator). Use populationVariance(double[], int, int)
for the non-bias-corrected
population variance.
See Variance
for
details on the computing algorithm.
Returns 0 for a single-value (i.e. length = 1) sample.
Throws MathIllegalArgumentException
if the array is null or the
array index parameters are not valid.
values
- the input arraybegin
- index of the first array element to includelength
- the number of elements to includeMathIllegalArgumentException
- if the array is null or the array index
parameters are not validpublic static double variance(double[] values, double mean, int begin, int length) throws MathIllegalArgumentException
Double.NaN
if the designated subarray is empty.
This method returns the bias-corrected sample variance (using n - 1
in
the denominator). Use populationVariance(double[], double, int, int)
for
the non-bias-corrected population variance.
See Variance
for
details on the computing algorithm.
The formula used assumes that the supplied mean value is the arithmetic mean of the sample data, not a known population parameter. This method is supplied only to save computation when the mean has already been computed.
Returns 0 for a single-value (i.e. length = 1) sample.
Throws MathIllegalArgumentException
if the array is null or the
array index parameters are not valid.
values
- the input arraymean
- the precomputed mean valuebegin
- index of the first array element to includelength
- the number of elements to includeMathIllegalArgumentException
- if the array is null or the array index
parameters are not validpublic static double variance(double[] values, double mean) throws MathIllegalArgumentException
Double.NaN
if the array
is empty.
This method returns the bias-corrected sample variance (using n - 1
in
the denominator). Use populationVariance(double[], double)
for the
non-bias-corrected population variance.
See Variance
for
details on the computing algorithm.
The formula used assumes that the supplied mean value is the arithmetic mean of the sample data, not a known population parameter. This method is supplied only to save computation when the mean has already been computed.
Returns 0 for a single-value (i.e. length = 1) sample.
Throws MathIllegalArgumentException
if the array is null.
values
- the input arraymean
- the precomputed mean valueMathIllegalArgumentException
- if the array is nullpublic static double populationVariance(double... values) throws MathIllegalArgumentException
Double.NaN
if the array is empty.
See Variance
for
details on the formula and computing algorithm.
Returns 0 for a single-value (i.e. length = 1) sample.
Throws MathIllegalArgumentException
if the array is null.
values
- the input arrayMathIllegalArgumentException
- if the array is nullpublic static double populationVariance(double[] values, int begin, int length) throws MathIllegalArgumentException
Double.NaN
if the designated subarray
is empty.
See Variance
for
details on the computing algorithm.
Returns 0 for a single-value (i.e. length = 1) sample.
Throws MathIllegalArgumentException
if the array is null or the
array index parameters are not valid.
values
- the input arraybegin
- index of the first array element to includelength
- the number of elements to includeMathIllegalArgumentException
- if the array is null or the array index
parameters are not validpublic static double populationVariance(double[] values, double mean, int begin, int length) throws MathIllegalArgumentException
Double.NaN
if the designated subarray is empty.
See Variance
for
details on the computing algorithm.
The formula used assumes that the supplied mean value is the arithmetic mean of the sample data, not a known population parameter. This method is supplied only to save computation when the mean has already been computed.
Returns 0 for a single-value (i.e. length = 1) sample.
Throws MathIllegalArgumentException
if the array is null or the
array index parameters are not valid.
values
- the input arraymean
- the precomputed mean valuebegin
- index of the first array element to includelength
- the number of elements to includeMathIllegalArgumentException
- if the array is null or the array index
parameters are not validpublic static double populationVariance(double[] values, double mean) throws MathIllegalArgumentException
Double.NaN
if the array is empty.
See Variance
for
details on the computing algorithm.
The formula used assumes that the supplied mean value is the arithmetic mean of the sample data, not a known population parameter. This method is supplied only to save computation when the mean has already been computed.
Returns 0 for a single-value (i.e. length = 1) sample.
Throws MathIllegalArgumentException
if the array is null.
values
- the input arraymean
- the precomputed mean valueMathIllegalArgumentException
- if the array is nullpublic static double max(double... values) throws MathIllegalArgumentException
Double.NaN
if the array is empty.
Throws MathIllegalArgumentException
if the array is null.
NaN
iff all values are NaN
(i.e. NaN
values have no impact on the value of the statistic).Double.POSITIVE_INFINITY
,
the result is Double.POSITIVE_INFINITY.
values
- the input arrayMathIllegalArgumentException
- if the array is nullpublic static double max(double[] values, int begin, int length) throws MathIllegalArgumentException
Double.NaN
if the designated subarray is empty.
Throws MathIllegalArgumentException
if the array is null or
the array index parameters are not valid.
NaN
iff all values are NaN
(i.e. NaN
values have no impact on the value of the statistic).Double.POSITIVE_INFINITY
,
the result is Double.POSITIVE_INFINITY.
values
- the input arraybegin
- index of the first array element to includelength
- the number of elements to includeMathIllegalArgumentException
- if the array is null or the array index
parameters are not validpublic static double min(double... values) throws MathIllegalArgumentException
Double.NaN
if the array is empty.
Throws MathIllegalArgumentException
if the array is null.
NaN
iff all values are NaN
(i.e. NaN
values have no impact on the value of the statistic).Double.NEGATIVE_INFINITY
,
the result is Double.NEGATIVE_INFINITY.
values
- the input arrayMathIllegalArgumentException
- if the array is nullpublic static double min(double[] values, int begin, int length) throws MathIllegalArgumentException
Double.NaN
if the designated subarray is empty.
Throws MathIllegalArgumentException
if the array is null or
the array index parameters are not valid.
NaN
iff all values are NaN
(i.e. NaN
values have no impact on the value of the statistic).Double.NEGATIVE_INFINITY
,
the result is Double.NEGATIVE_INFINITY.
values
- the input arraybegin
- index of the first array element to includelength
- the number of elements to includeMathIllegalArgumentException
- if the array is null or the array index
parameters are not validpublic static double percentile(double[] values, double p) throws MathIllegalArgumentException
p
th percentile of the values
in the values
array.
Double.NaN
if values
has length
0
p
) values[0]
if values
has length 1
IllegalArgumentException
if values
is null or p is not a valid quantile value (p must be greater than 0
and less than or equal to 100)
See Percentile
for a description of the percentile estimation algorithm used.
values
- input array of valuesp
- the percentile value to computeMathIllegalArgumentException
- if values
is null or p is invalidpublic static double percentile(double[] values, int begin, int length, double p) throws MathIllegalArgumentException
p
th percentile of the values
in the values
array, starting with the element in (0-based)
position begin
in the array and including length
values.
Double.NaN
if length = 0
p
) values[begin]
if length = 1
MathIllegalArgumentException
if values
is null, begin
or length
is invalid, or
p
is not a valid quantile value (p must be greater than 0
and less than or equal to 100)
See Percentile
for a description of the percentile estimation algorithm used.
values
- array of input valuesp
- the percentile to computebegin
- the first (0-based) element to include in the computationlength
- the number of array elements to includeMathIllegalArgumentException
- if the parameters are not valid or the input array is nullpublic static double sumDifference(double[] sample1, double[] sample2) throws MathIllegalArgumentException
sample1
- the first arraysample2
- the second arrayMathIllegalArgumentException
- if the arrays do not have the same (positive) length.MathIllegalArgumentException
- if the sample arrays are empty.public static double meanDifference(double[] sample1, double[] sample2) throws MathIllegalArgumentException
sample1
- the first arraysample2
- the second arrayMathIllegalArgumentException
- if the arrays do not have the same (positive) length.MathIllegalArgumentException
- if the sample arrays are empty.public static double varianceDifference(double[] sample1, double[] sample2, double meanDifference) throws MathIllegalArgumentException
sample1
- the first arraysample2
- the second arraymeanDifference
- the mean difference between corresponding entriesMathIllegalArgumentException
- if the arrays do not have the same length.MathIllegalArgumentException
- if the arrays length is less than 2.meanDifference(double[],double[])
public static double[] normalize(double... sample)
sample
- Sample to normalize.public static double[] mode(double... sample) throws MathIllegalArgumentException
The mode is the most frequently occurring value in the sample. If there is a unique value with maximum frequency, this value is returned as the only element of the output array. Otherwise, the returned array contains the maximum frequency elements in increasing order.
For example, if sample
is {0, 12, 5, 6, 0, 13, 5, 17},
the returned array will have length two, with 0 in the first element and
5 in the second.
NaN values are ignored when computing the mode - i.e., NaNs will never appear in the output array. If the sample includes only NaNs or has length 0, an empty array is returned.
sample
- input dataMathIllegalArgumentException
- if the indices are invalid or the array is nullpublic static double[] mode(double[] sample, int begin, int length)
The mode is the most frequently occurring value in the sample. If there is a unique value with maximum frequency, this value is returned as the only element of the output array. Otherwise, the returned array contains the maximum frequency elements in increasing order.
For example, if sample
is {0, 12, 5, 6, 0, 13, 5, 17},
the returned array will have length two, with 0 in the first element and
5 in the second.
NaN values are ignored when computing the mode - i.e., NaNs will never appear in the output array. If the sample includes only NaNs or has length 0, an empty array is returned.
sample
- input databegin
- index (0-based) of the first array element to includelength
- the number of elements to includeMathIllegalArgumentException
- if the indices are invalid or the array is nullCopyright © 2016–2017 Hipparchus.org. All rights reserved.