Sunday, July 19, 2009

Exponential density 3

In example 4.20 of Grinstead and Snell there is a nice conjunction of Bayes theorem and use of the exponential density. Recall that the exponential pdf is:

To find the probability that X happens (hard-drive failure, radioactive decay) within a certain time period, we integrate the pdf over the interval. For example, the probability that the failure happens after a particular time t is:

(Naturally, since the cdf(t) is 1 minus this value).

Here is one form of Bayes theorem:

Now, consider two events E and F defined as follows:

E is the event that failure happens after time r
F is the event that failure happens after time r + s

Note that P(F and E) = P(F) because F is totally contained within E.


The probability of failure after time r + s, when we know that failure occurs after time r, does not depend on r at all but is only a function of s. This is the memoryless property of the exponential function, alluded to in a previous post.

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