By I Ekeland

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**Extra info for Analyse convexe et problemes variationnels**

**Sample text**

Furthermore, assume that these random variables are independent1 . 3 for a formal deﬁnition of dependence. 3 Taxonomy of distributions 27 The non-central gamma distribution with degrees of freedom is deﬁned as the distribution of the following variable: [ \12 + · · · + \2 . 106) ¢ the non-central gamma distribution depends on three parameters ¡As such, > > 2 . The parameter is an integer and is called the degrees of freedom of the gamma distribution; the parameter can assume any value and is called the non-centrality parameter ; the parameter 2 is a positive scalar and is called the scale parameter.

10 for a few examples. Properties We can write (2=30) as follows: iX ({1 > = = = > {Q ) = iU (I[1 ({1 ) > = = = > I[Q ({Q )) Q Y i[q ({q ) . 33) q=1 This expression formalizes the loose expression (2=19): the joint pdf of a generic variable X is the product of the pdf of its copula and the pdf of the marginal densities of its entries. In other words, the copula factors out the purely marginal features of a distribution. The copula contains all the information about the joint features of a distribution in a standardized form.

6. 1 Uniform distribution The uniform distribution models the situation where the realization of the random variable [ is bound to take place on an interval [d> e] and all the values within that interval are equally likely outcomes of the measurement of [. We use the following notation to indicate that [ is uniformly distributed on the interval [d> e]: [ U ([d> e]) . 3 Taxonomy of distributions 17 Equivalent representations pdf f a U,b x cd f F a U,b x values o f X a b Fig. 5. 5. 5. 57) see Abramowitz and Stegun (1974).