Many of the currently known models for bivariate (multivariate) extreme value distributions are too restrictive. This paper introduces a new model based on polynomial terms that overcomes most weaknesses of the known models. The simplicity and exibility of the new model are shown by derivation of va
Specifying bivariate distributions by polynomial regressions
β Scribed by Wlodzimierz Bryc
- Publisher
- Elsevier Science
- Year
- 2000
- Tongue
- English
- Weight
- 74 KB
- Volume
- 47
- Category
- Article
- ISSN
- 0167-7152
No coin nor oath required. For personal study only.
β¦ Synopsis
We consider pairs of random variables X; Y with the property that regressions E(X n |Y ); E(Y n |X ) are polynomial. We show that the leading terms of these polynomials and the marginal distributions determine uniquely the bivariate distribution.
π SIMILAR VOLUMES
In this paper, we are concerned with bivariate di erentiable models for joint extremes for dependent data sets. This question is often raised in hydrology and economics when the risk driven by two (or more) factors has to be quantiΓΏed. Here we give a full characterization of polynomial models by mea
Problems of specifying bivariate discrete distributions by a conditional distribution and a regression function are investigated. A review of the known results, together with new characterizations involving conditional power series laws, is given. Also some remarks on a method making use of marginal