K-distribution

About: K-distribution is a research topic. Over the lifetime, 1281 publications have been published within this topic receiving 51774 citations.

Coherent states and Bayesian duality

Abstract: We demonstrate how large classes of discrete and continuous statistical distributions can be incorporated into coherent states, using the concept of a reproducing kernel Hilbert space. Each family of coherent states is shown to contain, in a sort of duality, which resembles an analogous duality in Bayesian statistics, a discrete probability distribution and a discretely parametrized family of continuous distributions. It turns out that nonlinear coherent states, of the type widely studied in quantum optics, are a particularly useful class of coherent states from this point of view, in that they contain many of the standard statistical distributions. We also look at vector coherent states and multidimensional coherent states as carriers of mixtures of probability distributions and joint probability distributions.

Folded- and Log-Folded-t Distributions as Models for Insurance Loss Data

Abstract: A rich variety of probability distributions has been proposed in the actuarial literature for fitting of insurance loss data. Examples include: lognormal, log-t, various versions of Pareto, loglogistic, Weibull, gamma and its variants, and generalized beta of the second kind distributions, among others. In this paper, we supplement the literature by adding the log-folded-normal and log-folded-t families. Shapes of the density function and key distributional properties of the 'folded' distributions are presented along with three methods for the estimation of parameters: method of maximum likelihood, method of moments, and method of trimmed moments. Further, large- and small-sample properties of these estimators are studied in detail. Finally, we fit the newly proposed distributions to data which represent the total damage done by 827 fires in Norway for the year 1988. The fitted models are then employed in a few quantitative risk management examples, where point and interval estimates for several value-at-risk measures are calculated.

Dynamic Interpolation Search Revisited

Abstract: A new dynamic Interpolation Search (IS) data structure is presented that achieves O(loglogn) search time with high probability on unknown continuous or even discrete input distributions with measurable probability of key collisions, including power law and Binomial distributions. No such previous result holds for IS when the probability of key collisions is measurable. Moreover, our data structure exhibits 0(1) expected search time with high probability for a wide class of input distributions that contains all those for which o(log log n) expected search time was previously known.

Non‐Gaussian probability distributions for a vortex fluid

Abstract: A system of N two‐dimensional vortices interacting in a bounded region can be described by the statistics of the coordinates of the vortices or by the statistics of the Fourier coefficients of the vorticity field. It is shown that both descriptions give equivalent results. A high energy expression for the probability distribution function of the Fourier coefficients is derived and shown to be non‐Gaussian; it has at least two, and in some cases a continuum of, equal height maximum points corresponding to distinct, but equally probable, equilibrium states. Other stationary points previously thought to be metastable states are shown to be saddle points of the distribution function and hence unstable.