Serialized Form

Package org.hipparchus.stat

Class org.hipparchus.stat.Frequency

class Frequency extends Object implements Serializable

serialVersionUID:

20160322L

Serialized Fields

freqTable

NavigableMap<T extends Comparable<T>,Long> freqTable

underlying collection

Class org.hipparchus.stat.LongFrequency

class LongFrequency extends Frequency<Long> implements Serializable

serialVersionUID:

20160322L

Package org.hipparchus.stat.descriptive

Class org.hipparchus.stat.descriptive.DescriptiveStatistics

class DescriptiveStatistics extends Object implements Serializable

serialVersionUID:

20160411L

Serialized Fields

eDA

ResizableDoubleArray eDA

Stored data values.

geometricMeanImpl

UnivariateStatistic geometricMeanImpl

Geometric mean statistic implementation.

kurtosisImpl

UnivariateStatistic kurtosisImpl

Kurtosis statistic implementation.

maxImpl

UnivariateStatistic maxImpl

Maximum statistic implementation.

meanImpl

UnivariateStatistic meanImpl

Mean statistic implementation.

minImpl

UnivariateStatistic minImpl

Minimum statistic implementation.

percentileImpl

Percentile percentileImpl

Percentile statistic implementation.

skewnessImpl

UnivariateStatistic skewnessImpl

Skewness statistic implementation.

sumImpl

UnivariateStatistic sumImpl

Sum statistic implementation.

sumOfSquaresImpl

UnivariateStatistic sumOfSquaresImpl

Sum of squares statistic implementation.

varianceImpl

UnivariateStatistic varianceImpl

Variance statistic implementation.

windowSize

int windowSize

holds the window size.

Class org.hipparchus.stat.descriptive.MultivariateSummaryStatistics

class MultivariateSummaryStatistics extends Object implements Serializable

serialVersionUID:

20160424L

Serialized Fields

covarianceImpl

VectorialCovariance covarianceImpl

Covariance statistic implementation

geoMeanImpl

StorelessMultivariateStatistic geoMeanImpl

Geometric mean statistic implementation

k

int k

Dimension of the data.

maxImpl

StorelessMultivariateStatistic maxImpl

Maximum statistic implementation

meanImpl

StorelessMultivariateStatistic meanImpl

Mean statistic implementation

minImpl

StorelessMultivariateStatistic minImpl

Minimum statistic implementation

n

long n

Count of values that have been added

sumImpl

StorelessMultivariateStatistic sumImpl

Sum statistic implementation

sumLogImpl

StorelessMultivariateStatistic sumLogImpl

Sum of log statistic implementation

sumSqImpl

StorelessMultivariateStatistic sumSqImpl

Sum of squares statistic implementation

Class org.hipparchus.stat.descriptive.StatisticalSummaryValues

class StatisticalSummaryValues extends Object implements Serializable

serialVersionUID:

20160406L

Serialized Fields

max

double max

The maximum value

mean

double mean

The sample mean

min

double min

The minimum value

n

long n

The number of observations in the sample

sum

double sum

The sum of the sample values

variance

double variance

The sample variance

Class org.hipparchus.stat.descriptive.StreamingStatistics

class StreamingStatistics extends Object implements Serializable

serialVersionUID:

20160422L

Serialized Fields

computeExtrema

boolean computeExtrema

whether or not min and max are maintained

computeMoments

boolean computeMoments

whether or not moment stats (sum, mean, variance) are maintained

computeSumOfLogs

boolean computeSumOfLogs

whether or not sum of logs and geometric mean are maintained

computeSumOfSquares

boolean computeSumOfSquares

whether or not sum of squares and quadratic mean are maintained

geoMeanImpl

GeometricMean geoMeanImpl

geoMean of values that have been added

maxImpl

Max maxImpl

max of values that have been added

meanImpl

Mean meanImpl

mean of values that have been added

minImpl

Min minImpl

min of values that have been added

n

long n

count of values that have been added

populationVariance

Variance populationVariance

population variance of values that have been added

randomPercentile

RandomPercentile randomPercentile

source of percentiles

secondMoment

SecondMoment secondMoment

SecondMoment is used to compute the mean and variance

sumImpl

Sum sumImpl

sum of values that have been added

sumOfLogsImpl

SumOfLogs sumOfLogsImpl

sumLog of values that have been added

sumOfSquaresImpl

SumOfSquares sumOfSquaresImpl

sum of the square of each value that has been added

varianceImpl

Variance varianceImpl

variance of values that have been added

Package org.hipparchus.stat.descriptive.moment

Class org.hipparchus.stat.descriptive.moment.GeometricMean

class GeometricMean extends AbstractStorelessUnivariateStatistic implements Serializable

serialVersionUID:

20150412L

Serialized Fields

incSumOfLogs

boolean incSumOfLogs

Determines whether or not this statistic can be incremented or cleared.

Statistics based on (constructed from) external statistics cannot be incremented or cleared.

sumOfLogs

SumOfLogs sumOfLogs

Wrapped SumOfLogs instance

Class org.hipparchus.stat.descriptive.moment.Kurtosis

class Kurtosis extends AbstractStorelessUnivariateStatistic implements Serializable

serialVersionUID:

20150412L

Serialized Fields

incMoment

boolean incMoment

Determines whether or not this statistic can be incremented or cleared.

Statistics based on (constructed from) external moments cannot be incremented or cleared.

moment

org.hipparchus.stat.descriptive.moment.FourthMoment moment

Fourth Moment on which this statistic is based

Class org.hipparchus.stat.descriptive.moment.Mean

class Mean extends AbstractStorelessUnivariateStatistic implements Serializable

serialVersionUID:

20150412L

Serialized Fields

incMoment

boolean incMoment

Determines whether or not this statistic can be incremented or cleared.

Statistics based on (constructed from) external moments cannot be incremented or cleared.

moment

org.hipparchus.stat.descriptive.moment.FirstMoment moment

First moment on which this statistic is based.

Class org.hipparchus.stat.descriptive.moment.SecondMoment

class SecondMoment extends org.hipparchus.stat.descriptive.moment.FirstMoment implements Serializable

serialVersionUID:

20150412L

Serialized Fields

m2

double m2

Second moment of values that have been added

Class org.hipparchus.stat.descriptive.moment.SemiVariance

class SemiVariance extends AbstractUnivariateStatistic implements Serializable

serialVersionUID:

20150412L

Serialized Fields

biasCorrected

boolean biasCorrected

Determines whether or not bias correction is applied when computing the value of the statistic. True means that bias is corrected.

varianceDirection

SemiVariance.Direction varianceDirection

Determines whether to calculate downside or upside SemiVariance.

Class org.hipparchus.stat.descriptive.moment.Skewness

class Skewness extends AbstractStorelessUnivariateStatistic implements Serializable

serialVersionUID:

20150412L

Serialized Fields

incMoment

boolean incMoment

Determines whether or not this statistic can be incremented or cleared.

Statistics based on (constructed from) external moments cannot be incremented or cleared.

moment

org.hipparchus.stat.descriptive.moment.ThirdMoment moment

Third moment on which this statistic is based

Class org.hipparchus.stat.descriptive.moment.StandardDeviation

class StandardDeviation extends AbstractStorelessUnivariateStatistic implements Serializable

serialVersionUID:

20150412L

Serialized Fields

variance

Variance variance

Wrapped Variance instance

Class org.hipparchus.stat.descriptive.moment.Variance

class Variance extends AbstractStorelessUnivariateStatistic implements Serializable

serialVersionUID:

20150412L

Serialized Fields

incMoment

boolean incMoment

Whether or not Variance.increment(double) should increment the internal second moment. When a Variance is constructed with an external SecondMoment as a constructor parameter, this property is set to false and increments must be applied to the second moment directly.

isBiasCorrected

boolean isBiasCorrected

Whether or not bias correction is applied when computing the value of the statistic. True means that bias is corrected. See Variance for details on the formula.

moment

SecondMoment moment

SecondMoment is used in incremental calculation of Variance

Package org.hipparchus.stat.descriptive.rank

Class org.hipparchus.stat.descriptive.rank.Max

class Max extends AbstractStorelessUnivariateStatistic implements Serializable

serialVersionUID:

20150412L

Serialized Fields

n

long n

Number of values that have been added

value

double value

Current value of the statistic

Class org.hipparchus.stat.descriptive.rank.Median

class Median extends AbstractUnivariateStatistic implements Serializable

serialVersionUID:

20150412L

Serialized Fields

percentile

Percentile percentile

The percentile impl to calculate the median.

Class org.hipparchus.stat.descriptive.rank.Min

class Min extends AbstractStorelessUnivariateStatistic implements Serializable

serialVersionUID:

20150412L

Serialized Fields

n

long n

Number of values that have been added

value

double value

Current value of the statistic

Class org.hipparchus.stat.descriptive.rank.Percentile

class Percentile extends AbstractUnivariateStatistic implements Serializable

serialVersionUID:

20150412L

Serialized Fields

cachedPivots

int[] cachedPivots

Cached pivots.

estimationType

Percentile.EstimationType estimationType

Any of the Percentile.EstimationTypes such as CM can be used.

kthSelector

KthSelector kthSelector

Default KthSelector used with default pivoting strategy

nanStrategy

NaNStrategy nanStrategy

NaN Handling of the input as defined by NaNStrategy

quantile

double quantile

Determines what percentile is computed when evaluate() is activated with no quantile argument.

Class org.hipparchus.stat.descriptive.rank.PSquarePercentile

class PSquarePercentile extends AbstractStorelessUnivariateStatistic implements Serializable

serialVersionUID:

20150412L

Serialized Fields

countOfObservations

long countOfObservations

Counter to count the values/observations accepted into this data set

initialFive

List<Double> initialFive

Initial list of 5 numbers corresponding to 5 markers. NOTE:watch out for the add methods that are overloaded

markers

PSquarePercentile.PSquareMarkers markers

Markers is the marker collection object which comes to effect only after 5 values are inserted

pValue

double pValue

Computed p value (i,e percentile value of data set hither to received)

quantile

double quantile

The quantile needed should be in range of 0-1. The constructor PSquarePercentile(double) ensures that passed in percentile is divided by 100.

Class org.hipparchus.stat.descriptive.rank.RandomPercentile

class RandomPercentile extends AbstractStorelessUnivariateStatistic implements Serializable

serialVersionUID:

1L

Serialized Fields

bufferMap

org.hipparchus.stat.descriptive.rank.RandomPercentile.BufferMap bufferMap

Data structure used to manage buffers

currentBuffer

org.hipparchus.stat.descriptive.rank.RandomPercentile.Buffer currentBuffer

Buffer currently being filled

epsilon

double epsilon

Bound on the quantile estimation error

h

int h

Maximum number of buffers minus 1

n

long n

Number of elements consumed from the input data stream

randomGenerator

RandomGenerator randomGenerator

Source of random data

s

int s

Storage size of each buffer

Package org.hipparchus.stat.descriptive.summary

Class org.hipparchus.stat.descriptive.summary.Product

class Product extends AbstractStorelessUnivariateStatistic implements Serializable

serialVersionUID:

20150412L

Serialized Fields

n

long n

The number of values that have been added

value

double value

The current Running Product

Class org.hipparchus.stat.descriptive.summary.Sum

class Sum extends AbstractStorelessUnivariateStatistic implements Serializable

serialVersionUID:

20150412L

Serialized Fields

n

long n

The number of values that have been added

value

double value

The currently running sum

Class org.hipparchus.stat.descriptive.summary.SumOfLogs

class SumOfLogs extends AbstractStorelessUnivariateStatistic implements Serializable

serialVersionUID:

20150412L

Serialized Fields

n

int n

Number of values that have been added

value

double value

The currently running value

Class org.hipparchus.stat.descriptive.summary.SumOfSquares

class SumOfSquares extends AbstractStorelessUnivariateStatistic implements Serializable

serialVersionUID:

20150412L

Serialized Fields

n

long n

Number of values that have been added

value

double value

The currently running sumSq

Package org.hipparchus.stat.descriptive.vector

Class org.hipparchus.stat.descriptive.vector.VectorialCovariance

class VectorialCovariance extends Object implements Serializable

serialVersionUID:

4118372414238930270L

Serialized Fields

isBiasCorrected

boolean isBiasCorrected

Indicator for bias correction.

n

long n

Number of vectors in the sample.

productsSums

double[] productsSums

Sums of products for each component.

sums

double[] sums

Sums for each component.

Class org.hipparchus.stat.descriptive.vector.VectorialStorelessStatistic

class VectorialStorelessStatistic extends Object implements Serializable

serialVersionUID:

20160413L

Serialized Fields

stats

StorelessUnivariateStatistic[] stats

Statistic for each component

Package org.hipparchus.stat.fitting

Class org.hipparchus.stat.fitting.EmpiricalDistribution

class EmpiricalDistribution extends AbstractRealDistribution implements Serializable

serialVersionUID:

5729073523949762654L

Serialized Fields

binCount

int binCount

number of bins

binStats

List<StreamingStatistics> binStats

List of SummaryStatistics objects characterizing the bins

delta

double delta

Grid size

loaded

boolean loaded

is the distribution loaded?

max

double max

Max loaded value

min

double min

Min loaded value

randomData

RandomDataGenerator randomData

RandomDataGenerator instance to use in repeated calls to getNext()

sampleStats

StreamingStatistics sampleStats

Sample statistics

upperBounds

double[] upperBounds

upper bounds of subintervals in (0,1) "belonging" to the bins

Package org.hipparchus.stat.regression

Class org.hipparchus.stat.regression.RegressionResults

class RegressionResults extends Object implements Serializable

serialVersionUID:

1L

Serialized Fields

containsConstant

boolean containsConstant

boolean flag indicator of whether a constant was included

globalFitInfo

double[] globalFitInfo

array storing global results, SSE, MSE, RSQ, adjRSQ

isSymmetricVCD

boolean isSymmetricVCD

boolean flag for variance covariance matrix in symm compressed storage

nobs

long nobs

number of observations on which results are based

parameters

double[] parameters

regression slope parameters

rank

int rank

rank of the solution

varCovData

double[][] varCovData

variance covariance matrix of parameters

Class org.hipparchus.stat.regression.SimpleRegression

class SimpleRegression extends Object implements Serializable

serialVersionUID:

-3004689053607543335L

Serialized Fields

hasIntercept

boolean hasIntercept

include an intercept or not

n

long n

number of observations

sumX

double sumX

sum of x values

sumXX

double sumXX

total variation in x (sum of squared deviations from xbar)

sumXY

double sumXY

sum of products

sumY

double sumY

sum of y values

sumYY

double sumYY

total variation in y (sum of squared deviations from ybar)

xbar

double xbar

mean of accumulated x values, used in updating formulas

ybar

double ybar

mean of accumulated y values, used in updating formulas