Scheduled System Maintenance on May 29th, 2015:
IEEE Xplore will be upgraded between 11:00 AM and 10:00 PM EDT. During this time there may be intermittent impact on performance. We apologize for any inconvenience.
By Topic

Theory and application of some classical and generalized asymptotic distributions of extreme values

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

1 Author(s)

An introduction is provided to the classical theory of asymptotic distributions of extreme values and to its application to estimation of tail probabilities. It is shown how the theory is sometimes misinterpreted to justify heuristic estimation procedures that introduce systematic error. A new generalized asymptotically convergent sequence of extreme-value distributions, differing from the classical sequence in higher order terms, which eventually disappear, is derived for the "exponential'' class of distributions. It is shown that in some cases of practical interest, the generalized sequence converges much faster to the asymptote than does the widely used classical sequence, and that tail-probability estimates of a given accuracy can be formulated from a much smaller number of data.

Published in:

Information Theory, IEEE Transactions on  (Volume:19 ,  Issue: 2 )