Journal Article10.2307/1968466
Metric spaces and completely monotone functions
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About: This article is published in Annals of Mathematics. The article was published on 01 Oct 1938. The article focuses on the topics: Convex metric space & Injective metric space.
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Citations
On Some Local, Global and Regularity Behaviour of Some Classes of Covariance Functions
Emilio Porcu,Michael L. Stein +1 more
- 01 Jan 2012
TL;DR: In this article, the authors summarize some of these proposed models and analyzes their local and global behaviour, both in terms of their covariance functions and the associated spectra, and describe some ways to obtain models allowing greater flexibility.
20
On Mixtures of Distributions: A Survey and Some New Results on Ranking and Selection
Shanti S Gupta,Wen-Tao Huang +1 more
- 01 Aug 1979
TL;DR: A survey of the literature dealing with mixtures of distributions can be found in this paper, where the topics covered relate to probabilistic properties, estimation, hypotheses testing and multiple decision (selection and ranking) procedures.
References
Metric spaces and positive definite functions
TL;DR: In this paper, a connection between the problem of isometric imbedding and the concept of positive definite functions has been made, and it has been shown that the possibility of topological imbeddability of (E in '&) is very easily expressible in terms of the elementary function e-t2 and positive definite function (Theorem 1) if this concept is properly enlarged.
Sur les fonctions absolument monotones
TL;DR: Les fonctions absolument monotones jouent le m~me rble fondamenta l duns la th6orie des f o n c t i o n s analytiques d 'une variable r6elle que les fonsctions (simplement) monotone for la classe g6n6rale des fonction £ variat ion born6e as mentioned in this paper.
492
•Book
Random variables and probability distributions
Harald Cramér
- 01 Jan 1937
TL;DR: In this paper, the authors introduce Axioms and preliminary theorems of the central limit theorem for stochastic processes and the normal distribution of the distribution in R1 and R2.
486