Partition entropy and chi-squared error: the improved MEMPHIS algorithm - Part I
Visualitza/Obre
Tipus de documentReport de recerca
Data publicació2009-07
Condicions d'accésAccés obert
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Reconeixement-NoComercial-SenseObraDerivada 3.0 Espanya
Abstract
The entropy of the population partition is studied as a function of
the sampling parameter, so that within a particular interval of its graph,
the plateau region, it is possible to get
a stable estimation of the mixture parameters. The optimal estimation is associated with a local maximum of entropy. Alter
natively,
the $\chi^2$ error of the mixture approach may also be used to obtain an optimal segregation. The
relationship between the fitting error and the population entropy has been
analysed in detail. We have proved that, by using an appropriate sampling parameter, within a plateau region of the entropy
graph,
a local entropy maximum takes place simultaneously with a local minimum of the $\chi^2$ error.
Therefore, the combined statistical method provides the best approximation mixture, as well as the less informative partiti
on,
to estimate the kinematic parameters of populations.
Fitxers | Descripció | Mida | Format | Visualitza |
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repentro2.pdf | Article principal | 197,2Kb | Visualitza/Obre |