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In the present paper we propose a multivariate version of the additive model of loss reserving.
The multivariate version of the skew-t distribution provides a powerful analytical description of the joint behavior of multivariate processes.
We develop here a multivariate version of the Bayes methodology for joint mapping of QTLs, using the Markov chain Monte Carlo (MCMC) algorithm.
The present paper introduces a notion of transorthogonality for a sequence of polynomial on Rd to extend the characterization to the multivariate version of the Letac Mora class of real natural exponential families.
Here, we consider the multivariate version of this problem: having n units which are classified according to q binary questions, we want to summarize the association between questions in terms of quasi-implications between features.
Now, we will provide the multivariate version of Theorem 2.2.
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In establishing its definition, the structural properties of both the bivariate and the multivariate versions of the generalized Waring distribution played a significant role.
This representation permits a direct simulation of the values of a random variable with PDF (1), which can be also used for generating multivariate versions of the BG distribution.
An interesting aspect of the bivariate and multivariate versions of the generalized Waring distribution is that their marginal distributions (conditional and unconditional) as well as their convolution are of the same form (UGWD's), properties that exhibit a symmetry analogous to that existing in the case of the multivariate normal distribution.
Multivariate versions of the breeder's equation are also possible (usually preferable, McGuigan 2006).
Multivariate versions of the DHGLM or reaction norm models with dummy environmental variables could be used to simultaneously investigate macro- and micro-environmental sensitivities when environments are discrete.
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