Powered by OpenAIRE graph
Found an issue? Give us feedback
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Norwegian Open Resea...arrow_drop_down
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
versions View all 1 versions
addClaim

Copula

Authors: Stenvik, Sigurd;
Abstract

Copulaen er et interessant verktøy i statistikken. Den er brukt i mange forskjellige områder fra finans til klimamodeller. En stor grunn til at copulaen er nyttig er hvordan man kan bruke copulaen til å splitte en bivariat fordeling opp i avhengighets-strukturen og selve marginalfordelingene. Vi vil forklare dette i denne oppgaven. Hvis du for første gang ser på definisjonen til copulaen kan det være vanskelig å forstå hva copulaen egentlig er. Derfor har vi gitt en foklaring på hva en copula er i form av sansynlighetsfordelinger, som burde være intuitiv for en person som allerde har litt kunnskap om statistikk. Vi skriver også om sklars teorem, som teoretisk forklarer denne sammenhengen mellom den bivariate fordelingen, dens marginalfordelinger og avhengighetsstrukturen mellom marginalfordelingene. Vi generaliserer også denne teorien fra $2$ til $n$ dimensjoner, og vi forklarer hvordan man kan estimere parameterne til en copula. Vi avslutter oppgaven med å vise hvordan man kan bruke en copula til å simulere fra en bivariat fordeling.

  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    0
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green