278 research outputs found
Online Sorting via Searching and Selection
In this paper, we present a framework based on a simple data structure and
parameterized algorithms for the problems of finding items in an unsorted list
of linearly ordered items based on their rank (selection) or value (search). As
a side-effect of answering these online selection and search queries, we
progressively sort the list. Our algorithms are based on Hoare's Quickselect,
and are parameterized based on the pivot selection method.
For example, if we choose the pivot as the last item in a subinterval, our
framework yields algorithms that will answer q<=n unique selection and/or
search queries in a total of O(n log q) average time. After q=\Omega(n) queries
the list is sorted. Each repeated selection query takes constant time, and each
repeated search query takes O(log n) time. The two query types can be
interleaved freely. By plugging different pivot selection methods into our
framework, these results can, for example, become randomized expected time or
deterministic worst-case time. Our methods are easy to implement, and we show
they perform well in practice
Fast computation of trimmed means
We present two methods of calculating trimmed means without sorting the data in O(n) time. The existing method implemented in major statistical packages relies on sorting, which takes O(n log n) time. The proposed algorithm is based on the quickselect algorithm for calculating order statistics with O(n) expected running time. It is an order of magnitude faster than the existing method for large data sets
Comment: Monitoring Networked Applications With Incremental Quantile Estimation
Our comments are in two parts. First, we make some observations regarding the
methodology in Chambers et al. [arXiv:0708.0302]. Second, we briefly describe
another interesting network monitoring problem that arises in the context of
assessing quality of service, such as loss rates and delay distributions, in
packet-switched networks.Comment: Published at http://dx.doi.org/10.1214/088342306000000600 in the
Statistical Science (http://www.imstat.org/sts/) by the Institute of
Mathematical Statistics (http://www.imstat.org
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