Generation of hierarchically correlated multivariate symbolic sequences

Physics – Computational Physics

Scientific paper

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

7 pages, 6 figures, 1 table

Scientific paper

10.1140/epjb/e2008-00225-7

We introduce an algorithm to generate multivariate series of symbols from a finite alphabet with a given hierarchical structure of similarities. The target hierarchical structure of similarities is arbitrary, for instance the one obtained by some hierarchical clustering procedure as applied to an empirical matrix of Hamming distances. The algorithm can be interpreted as the finite alphabet equivalent of the recently introduced hierarchically nested factor model (M. Tumminello et al. EPL 78 (3) 30006 (2007)). The algorithm is based on a generating mechanism that is different from the one used in the mutation rate approach. We apply the proposed methodology for investigating the relationship between the bootstrap value associated with a node of a phylogeny and the probability of finding that node in the true phylogeny.

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

Generation of hierarchically correlated multivariate symbolic sequences 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 Generation of hierarchically correlated multivariate symbolic sequences, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Generation of hierarchically correlated multivariate symbolic sequences will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFWR-SCP-O-108145

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