Infinite Divisibility and Max-Infinite Divisibility with Random Sample Size

Mathematics – Probability

Scientific paper

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

14 pages, in journal format. In the first sentence of the last paragraph on page 131 the part after the second comma was inadv

Scientific paper

Continuing the study reported in Satheesh (2001),(math.PR/0304499 dated 01 May 2003) and Satheesh (2002)(math.PR/0305030 dated 02May 2003), here we study generalizations of infinitely divisible (ID) and max-infinitely divisible (MID) laws. We show that these generalizations appear as limits of random sums and random maximums respectively. For the random sample size N, we identify a class of probability generating functions. Necessary and sufficient conditions that implies the convergence to an ID (MID) law by the convergence to these generalizations and vise versa are given. The results generalize those on ID and random ID laws studied previously in Satheesh (2001b, 2002) and those on geometric MID laws studies in Rachev and Resnick (1991). We discuss attraction and partial attraction in this generalization of ID and MID laws.

No associations

LandOfFree

Say what you really think

Search LandOfFree.com for scientists and scientific papers. Rate them and share your experience with other people.

Rating

Infinite Divisibility and Max-Infinite Divisibility with Random Sample Size does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Infinite Divisibility and Max-Infinite Divisibility with Random Sample Size, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Infinite Divisibility and Max-Infinite Divisibility with Random Sample Size will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFWR-SCP-O-703648

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.