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Characterization of characterization of joint density by conditional densities
Communications in Statistics - Theory and Methods, 1990In this paper the relationship between joint density and conditional densities is studied. An explicit formula is given for obtaining the joint density from the conditional ones. It is illustrated for the case of bivariate normal distribution.
A.K. Gupta, T. Varga
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On Density Conditions for Interpolation in the Ball
Canadian Mathematical Bulletin, 2003AbstractIn this paper we study interpolating sequences for two related spaces of holomorphic functions in the unit ball of Cn, n > 1. We first give density conditions for a sequence to be interpolating for the class A−∞ of holomorphic functions with polynomial growth.
Marco, Nicolas, Massaneda, Xavier
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A NOTE ON DENSITY AND THE DIRICHLET CONDITION
International Journal of Number Theory, 2012Motivated by topological approaches to Euclid and Dirichlet's theorems on infinitude of primes, we introduce and study [Formula: see text]-coprime topologies on a commutative ring R with an identity and without zero divisors. For infinite semiprimitive commutative domain R of finite character (i.e.
Marko, František, Porubský, Štefan
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Adaptive Estimation of a Conditional Density
International Statistical Review, 2015SummaryThe authors consider the problem of estimating a conditional density by a conditional kernel density estimate when the error associated with the estimate is measured by theL1‐norm. On the basis of the combinatorial method of Devroye and Lugosi (), they propose a method for selecting the bandwidths adaptively and for providing a theoretical ...
Bott, Ann-Kathrin, Kohler, Michael
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SVM method of estimating density, conditional probability, and conditional density
2000 IEEE International Symposium on Circuits and Systems. Emerging Technologies for the 21st Century. Proceedings (IEEE Cat No.00CH36353), 2002The problem of estimating density, conditional probability, and conditional density is considered as an ill-posed problem of solving integral equations. To solve these equations the support vector method (SVM) is used.
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