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A new method for building parametric-functional families of Lorenz curves, generated from an initial Lorenz curve (which satisfies some regularity conditions), is presented. The method is applied to the exponential family since they use the exponential Lorenz curves as their generating curves....
Persistent link: https://www.econbiz.de/10005738830
In this article, a new methodology for obtaining a premium based on a broad class of conjugate prior distributions, assuming lognormal claims, is presented. The new class of prior distributions arise in a natural way, using the conditional specification technique introduced by Arnold, Castillo,...
Persistent link: https://www.econbiz.de/10005324477
A k-dimensional density function is determined by certain combinations of marginal and conditional densities. The present paper identifies all possible such specifications. Gelman and Speed (1993) have treated the finite discrete case of this problem. The present paper extends their work to a...
Persistent link: https://www.econbiz.de/10005254862
It is well known that full knowledge of all conditional distributions will typically serve to completely characterize a bivariate distribution. Partial knowledge will often suffice. For example, knowledge of the conditional distribution of X given Y and the conditional mean of Y given X is often...
Persistent link: https://www.econbiz.de/10005006520
Distributions with normal conditionals have biquadratic regression functions. Consequently, in contrast to classical bivariate normal distributions, their densities can be multimodal. Criteria for determining the number of modes are discussed and illustrations of representative multimodal...
Persistent link: https://www.econbiz.de/10005053139
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Two new concepts of order statistics for multivariate samples are introduced. In one of the versions it turns out that not every multivariate order statistic is present in every sample. These order statistics have application in multivariate ranked set sampling and can be used to generate broad...
Persistent link: https://www.econbiz.de/10005006030
In this paper a special conjugate Bayesian method, for reconstructing and estimating traffic flows, based on α-shifted-Gamma <InlineEquation ID="IEq1"> <EquationSource Format="TEX">$$ \Upgamma (\theta ,\,\lambda ) $$</EquationSource> </InlineEquation> models <InlineEquation ID="IEq2"> <EquationSource Format="TEX">$$ H(\alpha ,\,\theta ,\,\lambda ) $$</EquationSource> </InlineEquation> is given. If the numbers of users traveling through different routes are assumed to...</equationsource></inlineequation></equationsource></inlineequation>
Persistent link: https://www.econbiz.de/10010989474