Topic
K-distribution
About: K-distribution is a research topic. Over the lifetime, 1281 publications have been published within this topic receiving 51774 citations.
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TL;DR: The Box-Cox elliptical distribution as mentioned in this paper provides alternative distributions for modeling multivariate positive, marginally skewed and possibly heavy-tailed data, and is interpretable in terms of quantiles and relative dispersions of the marginal distributions and associations between pairs of variables.
Abstract: We propose and study the class of Box-Cox elliptical distributions. It provides alternative distributions for modeling multivariate positive, marginally skewed and possibly heavy-tailed data. This new class of distributions has as a special case the class of log-elliptical distributions, and reduces to the Box-Cox symmetric class of distributions in the univariate setting. The parameters are interpretable in terms of quantiles and relative dispersions of the marginal distributions and of associations between pairs of variables. The relation between the scale parameters and quantiles makes the Box-Cox elliptical distributions attractive for regression modeling purposes. Applications to data on vitamin intake are presented and discussed.
3 citations
01 Jan 2006
TL;DR: The ability of the proposed distribution to model RF echographic signals from cardiac tissue and blood regions is demonstrated on data acquired in vivo.
Abstract: We study in this work the statistics of the radio frequency (RF) signal for both fully and partially developed speckle in echocardiographic images in the context of image segmentation and classification. From physical image formation model, we first derive the probability density function (pdf) of the RF signal using the K distribution framework. We then show that this pdf may be reliably approximated through a generalized Gaussian distribution. The ability of the proposed distribution to model RF echographic signals from cardiac tissue and blood regions is demonstrated on data acquired in vivo
3 citations
TL;DR: In this article, an elementary informal technique for deriving the convergence of known distributions to limiting normal or non-normal distributions is presented, which is of interest to teachers and students of first year graduate level courses in probability and statistics.
Abstract: This article presents an elementary informal technique for deriving the convergence of known distributions to limiting normal or non-normal distributions. The presentation should be of interest to teachers and students of first year graduate level courses in probability and statistics.
3 citations
Proceedings Article•
29 Jul 2010TL;DR: Four often used statistical models used to fit target and clutter regions in SAR data provided by MSTAR are assessed: the Weibull, Log-normal, Gamma and K distributions, and the results show that K distribution performs best and Log- normal performs worst for modeling clutter region.
Abstract: Accurate knowledge of statistical properties of SAR data plays an essential role in SAR image processing and understanding. Several studies have been made for discovering the relationship between the physical features and statistical properties of SAR data, and some statistical models for modeling SAR data having been proposed and studied. In this paper, we focused on four often used statistical models: the Weibull, Log-normal, Gamma and K distributions. These models are used to fit target and clutter regions in SAR data provided by MSTAR, and through three different goodness-of-fit tests, we assess the performance of the four statistical models for modeling the clutter and target in the SAR images. The results show that K distribution performs best and Log-normal performs worst for modeling clutter region, on the other hand, Log-normal distribution performs best while K distribution performs worst for modeling target region.
3 citations
Dissertation•
01 Jan 1997
3 citations