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Derive the formula for Monte Carlo Integration! When does MCI converge fast?
Given: values
distributed according to 
and samples of a function
: 


The more
, the smaller the variance of the quotient
,
thus MCI converges faster.


and samples of a function




The more


thus MCI converges faster.

Karteninfo:
Autor: janisborn
Oberthema: Informatik
Thema: Computergrafik
Schule / Uni: RWTH Aachen
Ort: Aachen
Veröffentlicht: 18.05.2022