Perhaps for now, the best is to copy the implementation of POISSON from
Commons-Math to POI,
but if we want to take more stuff I would seriously consider a jar
dependency.
I gave a quick look at what can be useful for POI. The left column is
Excel function, the right column is Math's implementation.
BETADIST org.apache.commons.math.distribution.BetaDistributionImpl
BINOMDIST
org.apache.commons.math.distribution.BinomialDistributionImpl
CHIDIST
org.apache.commons.math.distribution.ChiSquaredDistributionImpl
EXPONDIST
org.apache.commons.math.distribution.ExponentialDistributionImpl
FDIST org.apache.commons.math.distribution.FDistributionImpl
GAMMADIST org.apache.commons.math.distribution.GammaDistributionImpl
GEOMEAN org.apache.commons.math.stat.StatUtils#geometricMean
KURT org.apache.commons.math.stat.descriptive.moment.Kurtosis
NORMDIST org.apache.commons.math.distribution.NormalDistributionImpl
PEARSON
org.apache.commons.math.stat.correlation.PearsonsCorrelation
PERCENTILE org.apache.commons.math.stat.descriptive.rank.Percentile
TDIST org.apache.commons.math.distribution.TDistributionImpl
VAR org.apache.commons.math.stat.StatUtils#variance
There can be more.
Yegor
The code for POISSON should be stable over time. The poisson
distribution has a very simple definition that should be easy to test
(and we should). I guess the the complexity in the common-math
version is there for optimisation reasons. Unless we have better data
on how the Excel version of POISSON is generally used, we should
probably assume that the commons-math optimisations are appropriate.
In case it's not clear, I'm still in favour of copying over this small
amount of code from commons-math and maintaining it independently in
poi.
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