Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Polynomial probability distribution estimation using the method of moments
KTH, School of Industrial Engineering and Management (ITM), Production Engineering, Computer Systems for Design and Manufacturing.
2017 (English)In: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 12, no 4, e0174573Article in journal (Refereed) Published
Abstract [en]

We suggest a procedure for estimating Nth degree polynomial approximations to unknown (or known) probability density functions (PDFs) based on N statistical moments from each distribution. The procedure is based on the method of moments and is setup algorithmically to aid applicability and to ensure rigor in use. In order to show applicability, polynomial PDF approximations are obtained for the distribution families Normal, Log-Normal, Weibull as well as for a bimodal Weibull distribution and a data set of anonymized household electricity use. The results are compared with results for traditional PDF series expansion methods of Gram-Charlier type. It is concluded that this procedure is a comparatively simple procedure that could be used when traditional distribution families are not applicable or when polynomial expansions of probability distributions might be considered useful approximations. In particular this approach is practical for calculating convolutions of distributions, since such operations become integrals of polynomial expressions. Finally, in order to show an advanced applicability of the method, it is shown to be useful for approximating solutions to the Smoluchowski equation.

Place, publisher, year, edition, pages
PUBLIC LIBRARY SCIENCE , 2017. Vol. 12, no 4, e0174573
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:kth:diva-207692DOI: 10.1371/journal.pone.0174573ISI: 000399954800004PubMedID: 28394949Scopus ID: 2-s2.0-85017268619OAI: oai:DiVA.org:kth-207692DiVA: diva2:1103814
Note

QC 20170531

Available from: 2017-05-31 Created: 2017-05-31 Last updated: 2017-06-30Bibliographically approved

Open Access in DiVA

No full text

Other links

Publisher's full textPubMedScopus

Search in DiVA

By author/editor
Mattsson, Lars
By organisation
Computer Systems for Design and Manufacturing
In the same journal
PLoS ONE
Engineering and Technology

Search outside of DiVA

GoogleGoogle Scholar

Altmetric score

Total: 1 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf