The EGAN software is a functional implementation of a simple yet powerful paradigm for exploration of large empirical data sets downstream from computational analysis. By focusing on systems-level analysis via enrichment statistics, EGAN enables a human domain expert to transform high-throughput analysis results into hypergraph visualizations: concept maps that leverage the expert’s semantic un...

G. Herring, L. D. Carr, R. Carretero-González, P. G. Kevrekidis, and D. J. Frantzeskakis Department of Mathematics and Statistics, University of Massachusetts, Amherst, Massachusetts 01003-4515, USA Department of Physics, Colorado School of Mines, Golden, Colorado 80401, USA Nonlinear Dynamical Systems Group,* Department of Mathematics and Statistics, and Computational Science Research Center, ...

A general framework is presented for recursive computation of image local statistics in sliding window of almost arbitrary shape with “per-pixel” computational complexity substantially lower than the window size. As special cases, recursive algorithms are described for computing image local statistics such as local mean, local variance, local kurtosis, local order statistics (minimum, maximum, ...

In this paper, we consider robust control using randomized algorithms. We extend the existing order statistics distribution theory to the general case in which the distribution of population is not assumed to be continuous and the order statistics is associated with certain constraints. In particular, we derive an inequality on distribution for related order statistics. Moreover, we also propos...

D. Yan,1 R. Carretero-González,2 D. J. Frantzeskakis,3 P. G. Kevrekidis,1 N. P. Proukakis,4 and D. Spirn5 1Department of Mathematics and Statistics, University of Massachusetts Amherst, Amherst, Massachusetts 01003-4515, USA 2Nonlinear Dynamical Systems Group,* Computational Science Research Center and Department of Mathematics and Statistics, San Diego State University, San Diego, California 9...

We demonstrate the equivalence between commonly used test statistics for out-of-sample forecasting performance and conventional Wald statistics. This equivalence greatly simplifies the computational burden of calculating recursive out-of-sample test statistics and their critical values. Moreover, for the case with nested models we show that the limit distribution, which has previously been expr...

A new constant false alarm rate detector is proposed for ship detection in single-look and multilook intensity synthetic aperture radar images. The method is aimed at multiple target situations where the sea clutter statistics are estimated from a sample which is potentially contaminated by targets. It uses truncation to exclude outliers from the sample and truncated statistics to analyse the t...

We show how martingale techniques (both old and new) can be used to obtain otherwise hard-to-get information for the moments and distributions of waiting times for patterns in independent or Markov sequences. In particular, we show how these methods provide moments and distribution approximations for certain scan statistics, including about variable length scan statistics. Each general problem ...

Australia enjoys a high international reputation for research in experimental genetics, molecular and cell biology, animal and plant sciences, biotechnology, medicine, biodiversity, and ecological modelling. Computational research is broadly established in these domain areas and others relevant to bioscience. Combined with strong traditions in mathematics and statistics, and national and state ...

I n this paper, we investigate methods of reducing the computational complexity of the discrete cosine transform (DCT) in a software video encoder. The number of DCT calculations may be reduced by modeling the distribution of zero blocks. We demonstrate that the reduction in computational complexity is variable and depends on the statistics of the video sequence. We propose a new adaptive algor...