The Bivariate Lack-of-Memory Distributions
نویسندگان
چکیده
منابع مشابه
On Classification of Bivariate Distributions Based on Mutual Information
Among all measures of independence between random variables, mutual information is the only one that is based on information theory. Mutual information takes into account of all kinds of dependencies between variables, i.e., both the linear and non-linear dependencies. In this paper we have classified some well-known bivariate distributions into two classes of distributions based on their mutua...
متن کاملOn 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...
متن کاملAsymmetric Univariate and Bivariate Laplace and Generalized Laplace Distributions
Alternative specifications of univariate asymmetric Laplace models are described and investigated. A more general mixture model is then introduced. Bivariate extensions of these models are discussed in some detail, with particular emphasis on associated parameter estimation strategies. Multivariate versions of the models are briefly introduced.
متن کاملPeriodic Poisson Processes and Almost-lack-of-memory Distributions
Certain characterization properties of time-varying periodic Poisson flows are studied in terms of almost-lack-of-memory (ALM) distributions. Parameter estimation formulas are derived. A method for verifying the hypothesis on the membership of a sample to the class of ALM-distributions is developed. Algorithms for computing critical levels and power of the likelihood ratio test by the Monte Car...
متن کاملThe Canonical Decomposition of Bivariate Distributions P
The ordinary notion of a bivariate distribution has a natural generalisation. For this generalisation it is shown that a bivariate distribution can be characterised by a Hilbert space .%’ and a family da , 0 < p < 1, of subspaces of Z’. X specifies the marginal distributions whilst-X, is a summary of the dependence structure. This characterisation extends existing ideas on canonical correlation.
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Sankhya A
سال: 2017
ISSN: 0976-836X,0976-8378
DOI: 10.1007/s13171-017-0119-1