Talk:Importance sampling

From Wikipedia, the free encyclopedia

On January 21st, 2006, this article was expanded by Izar(199.111.224.202; I was logged out during editing). I am a 4th year undergraduate student in electrical engineering major, and my concentraion is communications and signal processing. As an undergraduate researcher, I am interested in information theory and coding theory.

Before I expand this article, it was a mathematics stub, so I added some sections. However, it still can be expanded in a lot of aspects. For example, for the biasing methods, there are many other kinds of them such as 'exponential twisting', so I think those can be explained briefly or with some details. Or, some applications using this importance sampling technique may be discussed in a different section. Izar 05:06, 21 January 2006 (UTC)

[edit] Introduction

I don't see why importance sampling is a variance reduction technique in MC estimation. It a technique for estimating E[X|A] when all you have is E[X|B]. If I remember correctly, it is the 'weighted importance sampling' techniques that have reduced variance compared to the standard 'importance sampling' technique, at the expense of becoming biased. --Olethros 16:15, 9 February 2006 (UTC)

[edit] Mathematical approach

Why is this talking about the binomial distribution and event (X>t)? Just talking about the expectation of a general random variable would have been much simpler and much more general. The X>t treatment is confusing and overlong.--Olethros 16:15, 9 February 2006 (UTC)

I totally agree! The edits by 199.111.224.202 [1] made the article very difficult to understand. Someone should really perform some cleanup here. --Fredrik Orderud 17:51, 9 February 2006 (UTC)