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Statistics
See:
Description
Class Summary  
BasicHistogram  Basic histogram of a random variable able to write ASCII character output which can then be processed by Scigraphica or gri (a graphics programming language) into a postscript histogram. 
ControlledRandomVariable  Class improving the convergence of conditional expectations in the class
RandomVariable by the use of control variates. 
EmpiricalDistribution  Container for data implementing a large number of efficient statistics. 
EmpiricalRandomVariable  A random variable X distributed according to the empirical distribution associated with a data sample. 
FinMath  This class contains static methods to compute functions or solve eqations * useful in basic financial mathematics. 
FixedBinDataSource  A non rebinnable container for data implementing the interface
jas.hist.Rebinnable1DHistogramData
defined in the JAS
library. 
LoopStatus  Provides methods to report the progress of a loop and project time to completion. 
PointDataSource  Class used to draw a single vertical line in a
jas.hist.JASHist histogram. 
PoissonVariable  The Poisson variable N with intensity (mean) lambda has values n>=0 * with probabilities p_n=Prob(N=n)=e^{lambda}*lambda^n/n!. 
Random  Provides static methods to generate random numbers based on the * cern.jet.random random number generators. 
RandomDataSource  A normalized FixedBinDataSource fed by the samples of a
random variable X conditioned on
information
available at time t. 
RandomVariable  This class implements methods to compute conditional and unconditional
expectations, standard deviations and other statistics and histograms of a
random variable X (this ). 
RandomVector  This class is the vectorial analogue of the class RandomVariable
and implements componentwise expectations and standard deviations as well as
covariations and correlations between components. 
RandVariable  A restricted version of the class RandomVariable providing
* only one method to compute the mean. 
Vector  Provides static methods for component by component operations on double[ ]s. 
Statistics
This is the main package defining RandomVariables
and
RandomVectors
. Each of these classes becomes concrete by defining
a single abstract method getValue(int t)
intepreted as the next
draw from the underlying distribution conditioned on all information available
at time t
. Typically this information is the state of the path
sε[0,t]> X(s)
of some stochastic process
X
up to time t
.
Random variables and vectors have a variety of methods to compute statistics associated with the underlying distribution. Histograms are also supported. Random vectors are necessary if we have to deal with correlations and have a method to compute the covariation matrix. One call to the underlying stochastic mechanism produces the next sample for each coordinate. Separate random variables make separate calls to the underlying stochastic mechanism and thus appear to be independent.
There is also a utility class FinMath
containing some
static methods which are useful in financial mathematics: the BlackScholes
formula, solving for implied volatlities, cumulative normal and inverse
cumulative normal distribution function etc.
The various data source
classes make the connection to the
jas
(java analyis studio) library to support the computation
and display of histograms.


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