Documentation API of the 'jhplot.stat.FactorialMoments' Java class
FactorialMoments
jhplot.stat

## Class FactorialMoments

• `public class FactorialMomentsextends Object`
Normalised factorial moments (NFM). They characterise local multiplicity fluctuations inside a restricted phase space. It can calculate factorial moments (getFM() method) or normalized factorial moment (getNFM() method). The original version with horizontal binning was proposed in: A.Bialas, R.Peschanski, Nucl. Phys. B273 (1986) 703 B308 (1988) 857
• ### Constructor Summary

Constructors
Constructor and Description
`FactorialMoments(int NmaxOrder, int Bins, int step, double Min, double Max)`
Initialize factorial-moment calculations.
• ### Method Summary

All Methods
Modifier and TypeMethod and Description
`void``doc()`
Show online documentation.
`boolean``eval()`
Evaluate factorial moments at the end of the run
`P1D``getAv()`
Return average multiplicity as a function of bin
`P1D``getFM(int order)`
Return factorial moments (without normalization): log(FM) as a function of number of bins.
`P1D``getNFM(int order)`
Return results: NFM as a function of number of bins.
`void``run(double[] v)`
Collect information about sampling.
• ### Methods inherited from class java.lang.Object

`equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait`
• ### Constructor Detail

• #### FactorialMoments

`public FactorialMoments(int NmaxOrder,                        int Bins,                        int step,                        double Min,                        double Max)`
Initialize factorial-moment calculations.
Parameters:
`NmaxOrder` - Maximum order of factorial moments for the calculations
`Bins` - Defines Max number of bins used to divide the phase space (>1). The actual number of divisions is step*Bins. Therefore, 10 bins with step=4 means 400 divisions between Min and Max
`step` - used to increase step for divisions
`Min` - Min value in X
`Max` - Max value in X
• ### Method Detail

• #### run

`public void run(double[] v)`
Collect information about sampling. Put this method in a loop and pass vector with particle characteristics.
Parameters:
`v` - - vector characterizing particles (like momentum, speed etc)
• #### eval

`public boolean eval()`
Evaluate factorial moments at the end of the run
Returns:
true if success
• #### getNFM

`public P1D getNFM(int order)`
Return results: NFM as a function of number of bins. The order should be >1 but smaller than 5;
Parameters:
`order` - order of normalized factorial moment (from 2-5)
Returns:
normalized factorial moment
• #### getFM

`public P1D getFM(int order)`
Return factorial moments (without normalization): log(FM) as a function of number of bins. The order should be >1 but smaller than 5;
Parameters:
`order` - order of factorial moment (from 2-10)
Returns:
factorial moment
• #### getAv

`public P1D getAv()`
Return average multiplicity as a function of bin
Returns:
average multiplicity in bins
• #### doc

`public void doc()`
Show online documentation.

DMelt 1.2 © DataMelt by jWork.ORG

FactorialMoments
jhplot.stat

## Class FactorialMoments

• `public class FactorialMomentsextends Object`
Normalised factorial moments (NFM). They characterise local multiplicity fluctuations inside a restricted phase space. It can calculate factorial moments (getFM() method) or normalized factorial moment (getNFM() method). The original version with horizontal binning was proposed in: A.Bialas, R.Peschanski, Nucl. Phys. B273 (1986) 703 B308 (1988) 857

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