Class StatisticsPRP

java.lang.Object
  |
  +--StatisticsPRP

class StatisticsPRP

extends java.lang.Object

The class contains various parametric and non-parametric probability statistics methods used in computing statistics for ProtPlot. These include: F-test, t-test, p-values for t-test, histogram, mean, stdDev, median, mode, extrema, etc.

NOTE: Statistics package (derived from MAExplorer, WebGel and GELLAB-II which were in turn derived from Numerical Recipes, and other sources).

This work was produced by Peter Lemkin of the National Cancer Institute, an agency of the United States Government and Djamel Medjahed (SAIC-Frederick). As a work of the United States Government there is no associated copyright. It is offered as open source software under the Mozilla Public License (version 1.1) subject to the limitations noted in the accompanying LEGAL file.

Version:

$Date: 2002/10/14 20:17:17 $ $Revision: $

Author:

P. Lemkin (NCI), Djamel Medjahed (SAIC), NCI-Frederick, Frederick, MD

See Also:

ProtPlot Home

This work was derived from MAExplorer under the Mozilla 1.1 Open Source Public License by Peter Lemkin of the National Cancer Institute, an agency of the United States Government subject to the limitations noted in the accompanying LEGAL file. See licence info on http://maexplorer.sourceforge.org/

Field Summary

(package private) float	deltaBinH width of the bins computed as: nBinsH/(maxDataH-minDataH)
(package private) double	dF CALC: degrees of freedom T or F test
(package private) double	dFks CALC: degrees of freedom KS-test
(package private) double	f CALC: calculated f statistic
(package private) double	fStat CALC: f-statistic
(package private) int[]	hist histogram of size [0:nBinsH-1]
(package private) double	ksD CALC: Kolmogorov-Smirnov D statistic
(package private) float	maxDataH max value in data[]
(package private) float	meanAbsDevH mean absolute deviation
(package private) float	meanH mean of data[]
(package private) int	meanIdx index of mean in hist[]
(package private) float	medianH
(package private) int	medianIdx index of median in hist[]
(package private) float	minDataH min value in data[]
(package private) float	modeH mode of data[]
(package private) int	modeIdx index of mode in hist[]
(package private) int	nBinsH 0 if none.
(package private) double	pF CALC: f-test p-value w/NULL hypoth
(package private) double	pKS CALC: Kolmogorov-Smirnov test p-value w/NULL hypoth
private static ProtPlot	prp instance of ProtPlot
(package private) double	pT CALC: t-test p-value w/NULL hypoth
(package private) float	stdDevH standard deviation of data[]
(package private) double	t CALC: t or t' statistic
(package private) java.lang.String	title for data used in histogram
(package private) char	useTest CALC: 'B' or 'T' - t-test to use
private static UtilPRP	util instance of UtilPRP

Constructor Summary

(package private)

StatisticsPRP(ProtPlot prP) StatisticsPRP() - constructor

Method Summary

(package private) boolean	calcFprobFromVariances(int n1, int n2, double var1, double var2) calcFprobFromVariances() - calculate 2-tailed f probility that variables are same.
(package private) int	calcHistStats(java.lang.String title, int nBins, float[] data, int nData) calcHistStats() - compute and analyze histogram generating statistics.
(package private) int	calcHistStats(java.lang.String title, int nBins, float[] data, int nData, int[] hist) calcHistStats() - compute and analyze a histogram for whatever range of data is given.
(package private) boolean	calcKS_DandPvalues(double[] data1, int n1, double[] data2, int n2) calcKS_DandPvalues() - calculate Kolmogorov-Smirnov ksD, pKS, dFks from (n1,data1) and (n2,data2).
(package private) boolean	calcTandPvalues(int n1, int n2, double m1, double m2, double s1, double s2) calcTandPvalues() - calculate f, t, p, dF from (n1,m1,s1) and (n2,m2,s2).

Methods inherited from class java.lang.Object

, clone, equals, finalize, getClass, hashCode, notify, notifyAll, registerNatives, toString, wait, wait, wait

Field Detail

prp

private static ProtPlot prp

instance of ProtPlot

util

private static UtilPRP util

instance of UtilPRP

dF

double dF

CALC: degrees of freedom T or F test

dFks

double dFks

CALC: degrees of freedom KS-test

useTest

char useTest

CALC: 'B' or 'T' - t-test to use

t

double t

CALC: t or t' statistic

pT

double pT

CALC: t-test p-value w/NULL hypoth

f

double f

CALC: calculated f statistic

pF

double pF

CALC: f-test p-value w/NULL hypoth

fStat

double fStat

CALC: f-statistic

ksD

double ksD

CALC: Kolmogorov-Smirnov D statistic

pKS

double pKS

CALC: Kolmogorov-Smirnov test p-value w/NULL hypoth

title

java.lang.String title

for data used in histogram

meanIdx

int meanIdx

index of mean in hist[]

medianIdx

int medianIdx

index of median in hist[]

modeIdx

int modeIdx

index of mode in hist[]

nBinsH

int nBinsH

0 if none. size of histogram

hist

int[] hist

histogram of size [0:nBinsH-1]

medianH

float medianH

modeH

float modeH

mode of data[]

meanH

float meanH

mean of data[]

stdDevH

float stdDevH

standard deviation of data[]

meanAbsDevH

float meanAbsDevH

mean absolute deviation

minDataH

float minDataH

min value in data[]

maxDataH

float maxDataH

max value in data[]

deltaBinH

float deltaBinH

width of the bins computed as: nBinsH/(maxDataH-minDataH)

Constructor Detail

StatisticsPRP

StatisticsPRP(ProtPlot prP)

StatisticsPRP() - constructor

Parameters:

prp - is ProtPlot instance

Method Detail

calcFprobFromVariances

boolean calcFprobFromVariances(int n1,
                               int n2,
                               double var1,
                               double var2)

calcFprobFromVariances() - calculate 2-tailed f probility that variables are same. It computes:

    fStat - the f-statistic
    pF    - CALC: probab. vars. same

Parameters:

n1 - # samples class 1

n2 - # samples class 2

var1 - variance of class 1

var2 - variance of class 2

Returns:

false if any problems.

See Also:

MathPRP.nr_betai(double, double, double)

calcTandPvalues

boolean calcTandPvalues(int n1,
                        int n2,
                        double m1,
                        double m2,
                        double s1,
                        double s2)

calcTandPvalues() - calculate f, t, p, dF from (n1,m1,s1) and (n2,m2,s2). Use Behrens-Fisher/Satterthwaite estimate for t and dF if f-stat is < 0.05 p-value that variances are different. Otherwise use the standard student t-statistic with DF= (n1+n2-2). If you want to force the test the set useTest to 'B' or 'T', else it will pick the test to use (ie. TB or TP). It uses the algorithm described Numerical Recipes in C (1st Ed) for estimating p-value given the t-statistic using the incomplete beta function betai(). It computes:

    f - calculated f statistic
    t - t or t' statistic
    pT - t-test p-value w/NULL hypoth
    pF - f-test p-value w/NULL hypoth
    dF - degrees of freedom
 

Parameters:

n1 - # samples in class 1

n2 - # samples in class 2

m1 - sample mean class 1

m2 - sample mean class 2

s1 - sample std dev class 1

s2 - sample std dev class 2

See Also:

MathPRP.nr_betai(double, double, double), calcFprobFromVariances(int, int, double, double)

calcKS_DandPvalues

boolean calcKS_DandPvalues(double[] data1,
                           int n1,
                           double[] data2,
                           int n2)

calcKS_DandPvalues() - calculate Kolmogorov-Smirnov ksD, pKS, dFks from (n1,data1) and (n2,data2). DF= (n1+n2-2). It computes:

    ksD - D statistic
    pKS - KS test p-value w/NULL hypoth
    dFks - degrees of freedom
 

Parameters:

data1 - sample data class 1

n1 - # samples in class 1

data2 - sample data class 2

n2 - # samples in class 2

calcHistStats

int calcHistStats(java.lang.String title,
                  int nBins,
                  float[] data,
                  int nData)

calcHistStats() - compute and analyze histogram generating statistics. for whatever range of data is given. This computes and returns the results in variables of this instance: hist[0:nBins-1], medianH, modeH, meanH, stdDevH, meanAbsDevH, minDataH, maxDataH, deltaBinH

Parameters:

title - for data

nBins - size of hist[]

data - of size [0:nData-1]

nData - size of data array

Returns:

nBins if successful.

See Also:

calcHistStats(java.lang.String, int, float[], int)

calcHistStats

int calcHistStats(java.lang.String title,
                  int nBins,
                  float[] data,
                  int nData,
                  int[] hist)

calcHistStats() - compute and analyze a histogram for whatever range of data is given. This computes and returns the results in variables of this instance:

   hist[0:nBins-1], medianH, modeH, meanH,
   stdDevH, meanAbsDevH, minDataH, maxDataH, deltaBinH.

Note: if hist is int[nBins+1], then it will not be allocated.

Parameters:

title - for data

nBins - size of hist[]

data - of size [0:nData-1]

nData - size of data array

hist - opt. [nBins+1] else null in which case it will allocate it locally

Returns:

nBins if successful else 0.