Optimal estimate of probability density functions from experimental data

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dc.creatorLabbé, R.
dc.date2007-05-29
dc.date.accessioned2026-07-07T08:03:32Z
dc.date.available2026-07-07T08:03:32Z
dc.descriptionA method providing optimal estimate of probability density functions (PDFs) from time series is proposed. It allows almost arbitrary resolution PDFs when applied to either, sampled analytic functions or digitized data from experiments. When results are compared with PDFs of the same data calculated using the standard histogram method, a remarkable improvement is observed, especially in far lateral regions of the PDF, where low probability events give poor statistics.
dc.description3 pages, 2 figures
dc.identifierhttps://arxiv.org/abs/0705.4278
dc.identifierhttp://arxiv.org/abs/0705.4278
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/129614
dc.subjectData Analysis, Statistics and Probability
dc.titleOptimal estimate of probability density functions from experimental data
dc.typetext

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