search for: nlogn

...ity seems to go up in O(n). UPPER = 1e6 TIME < 1 second UPPER = 1e7 TIME = 7 seconds UPPER = 1e8 TIME = 95 seconds (UPPER = 1e9 didn't run because of memory allocation error). Am I right in these observations? If I am right, are there ways to speed up the weighted bootstrap sampling to O(nlogn), for instance? Thanks in advance! -- Jonathan Q. Li, PhD Agilent Technologies Laboratory Palo Alto, California, USA -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info"...

...the main bottleneck of BWT and really significant progress has been made in this area since the first algorithms of Manbers and Myers[2] and Larsson and Sadakane[3], notably the new linear time algorithms of Karkkainen and Sanders[4]; Kim, Sim and Park[5] and Ko e aluru[6] and also the promising O(nlogn) algorithm of Karkkainen and Burkhardt[7]. As a conjecture, we believe that some intrinsic properties of ZFS and file systems in general (e.g. sparseness and data entropy in blocks) could be exploited in order to produce brand new and really efficient compression algorithms, as well as the adaptat...

If anyone has a very fast vectorized method for doing the following I would appreciate some help. I want to avoid outer() to limit memory problems for very large n. Let x = real vector of length n y = real vector of length n w = real vector of length m, m typically less than n/2 but can be > n z = real vector of length m For w[i], i=1,,,m, find the value of x that is closest to w[i]. In