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Titolo:
On probability distribution functions in turbulence. Part 1. A regularisation method to improve the estimate of a PDF from an experimental histogram
Autore:
Andreotti, B; Douady, S;
Indirizzi:
Univ Paris 06, Ecole Normale Super, Lab Plast Stat, Lab CNRS, F-75231 Paris 05, France Univ Paris 06 Paris France 05 t Stat, Lab CNRS, F-75231 Paris 05, France Univ Paris 07, Ecole Normale Super, Lab Plast Stat, Lab CNRS, F-75231 Paris, France Univ Paris 07 Paris France F-75231 Stat, Lab CNRS, F-75231 Paris, France
Titolo Testata:
PHYSICA D
fascicolo: 1-2, volume: 132, anno: 1999,
pagine: 111 - 132
SICI:
0167-2789(19990715)132:1-2<111:OPDFIT>2.0.ZU;2-B
Fonte:
ISI
Lingua:
ENG
Keywords:
statistics; probability distribution function; turbulence;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
Physical, Chemical & Earth Sciences
Citazioni:
8
Recensione:
Indirizzi per estratti:
Indirizzo: Andreotti, B Univ Paris 06, Ecole Normale Super, Lab Plast Stat, Lab CNRS,24 Rue Lhomond, F-75231 Paris 05, France Univ Paris 06 24 Rue Lhomond Paris France 05 aris 05, France
Citazione:
B. Andreotti e S. Douady, "On probability distribution functions in turbulence. Part 1. A regularisation method to improve the estimate of a PDF from an experimental histogram", PHYSICA D, 132(1-2), 1999, pp. 111-132

Abstract

The most common method to estimate a probability distribution function (PDF) from experimental data is to compute a normalised histogram. This approximation implicitly assumes that the PDF is smooth at the scale of one histogram bin. Usually, the normalised histogram is ill defined for the rarer events since the points are very scattered in that region. In order to increase the quality of the PDF estimate, the assumption that the PDF is smooth can be used explicitly. A specially designed regularisation method is constructed and tested on both synthetic and real turbulence signals. Using this procedure, the estimated PDFs are now smooth and well-defined up to the unique rarest event (the last histogram point). Among its direct applications,the method allows to get a better estimate of high order PDF moments and of PDFs convolution products. (C) 1999 Elsevier Science B.V. All rights reserved.

ASDD Area Sistemi Dipartimentali e Documentali, Università di Bologna, Catalogo delle riviste ed altri periodici
Documento generato il 29/11/20 alle ore 15:57:51