ON SELECTION PROCEDURES FOR EXPONENTIAL DISTRIBUTIONS

Portfolio selection based on upper and lower exponential possibility distributions

In this paper, two kinds of possibility distributions, namely, upper and lower possibility distributions are identi®ed to re ̄ect experts' knowledge in portfolio selection problems. Portfolio selection models based on these two kinds of distributions are formulated by quadratic programming problems. It can be said that a portfolio return based on the lower possibility distribution has smaller po...

Some New Characterization Results on Exponential and Related Distributions

On Bivariate Generalized Exponential-Power Series Class of Distributions

In this paper, we introduce a new class of bivariate distributions by compounding the bivariate generalized exponential and power-series distributions. This new class contains the bivariate generalized exponential-Poisson, bivariate generalized exponential-logarithmic, bivariate generalized exponential-binomial and bivariate generalized exponential-negative binomial distributions as specia...

Exponential and Piecewise Exponential Distributions

Since lifetimes are almost always non-negative, the normal model/distribution may not be appropriate. An easy to use, positive distribution is the exponential distribution. To a less extend, exponential distributions to the survival analysis is like normal distributions to the linear model/ANOVA. Piecewise exponential distribution is also used to bridge/connect the parametric and nonparametric ...

UCB Algorithm for Exponential Distributions

We introduce in this paper a new algorithm for Multi-Armed Bandit (MAB) problems. A machine learning paradigm popular within Cognitive Network related topics (e.g., Spectrum Sensing and Allocation). We focus on the case where the rewards are exponentially distributed, which is common when dealing with Rayleigh fading channels. This strategy, named Multiplicative Upper Confidence Bound (MUCB), a...