Independent random variables
A bound on the 2-Wasserstein distance between linear combinations of independent random variables
... Aside from the variance-gamma case discussed in [12, 9], there are several other recent references where versions of (1.4) and (1.8) are proposed for complicated probability distributions such as the Kummer-U ...
31
Malliavin calculus and Dirichlet structures for independent random variables
... for independent random variables The motivation to develop a Malliavin calculus for independent random variables was ...of independent, non necessarily identically ...
178
Concentration for independent random variables with heavy tails
... This section provides an equivalent form of the weak Poincar´e inequality, in terms of a comparison between capacity of sets and their measure.. This point of view was put forward in [3][r] ...
20
Condensation and extremes for a fluctuating number of independent random variables
... of random allocation models and zrp, when the distribution of occupations is ...distributed random variables conditioned by the value of their ...of random variables used all throughout ...
55
Malliavin and Dirichlet structures for independent random variables
... E [L1F (X)] = E [F ′′ (X) Λ(X)] , which means that we are reduced to estimate how far Λ is from the constant random variable equal to 1. This kind of identity, where the second order derivative is multiplied by a ...
46
Discrete-time risk models based on time series for count random variables.
... Keywords : Discrete-time risk model; Poisson MA(1) process; Poisson AR(1) process; Markov Bernoulli Process; Markovian Environment; Lundberg Coe¢ cient. 1 Introduction We consider the portfolio of an insurance company in ...
28
Approximating the Probability Distribution of Functions of Random Variables: A New Approach
... 1 Introduction Many statistical models involve functional transformations of random variables. Regression models with stochastic regressors are the most common example, involving a linear transformation of ...
22
Cramér theorem for Gamma random variables
... strongly independent random ...strongly independent random variables (actually the implication ii) → i) in these results, whose proof is based on the differential equation satisfied by ...
15
On the outlying eigenvalues of a polynomial in large independent random matrices
... are independent standard ...these variables are merely independent and identically dis- tributed with a finite fourth ...classical random matrix models, the seminal paper being [7], where the ...
38
Large deviation results for triangular arrays of semiexponential random variables
... {λy − Λ Y (λ)}. Note that we recover the same asymptotics as for the non truncated random variable Y . In other words, the truncation does not impact the deviation behaviour. Now we consider the case where log P(Y ...
21
Co-clustering of ordinal data via latent continuous random variables and not missing at random entries
... Abstract This paper is about the co-clustering of ordinal data. Such data are very common on e-commerce platforms where customers rank the products/services they bought. More in details, we focus on arrays of ordinal ...
35
A perspective on the extension of stochastic orderings to fuzzy random variables
... tive random set theory. A fuzzy random variable is then viewed as a random conjunctive fuzzy set, ...classical random variable ranging in a set of (mem- bership) ...of random fuzzy ...
8
Asymptotic distribution of circularity coefficients estimate of complex random variables
... [6] J. Eriksson and V. Koivunen, "Complex random vectors and ICA models: identifiability, uniqueness, and separability,” IEEE Trans. Inform. Theory, vol. 52 no. 3, pp. 1017-1029, March 2006. [7] P.J. Schreier, ...
12
Combining clustering of variables and feature selection using random forests
... 1 Introduction This paper addresses the problems of dimension reduction and variable selection in the context of supervised classification. In this framework, there are often two objectives : prediction (to be able to ...
24
REGULAR VARIATION OF A RANDOM LENGTH SEQUENCE OF RANDOM VARIABLES AND APPLICATION TO RISK ASSESSMENT
... is the ruin probability on a finite-time horizon that is the probability that the supremum of the process S exceeds a threshold on a time window [0, T ], for a given T > 0. It is straightforward that maxima ...
23
Two properties of vectors of quadratic forms in Gaussian random variables
... 1) random variables η1, ...the variables Fi are necessarily linearly dependent when F is not absolutely continuous, as the following simple counterexample ...
15
Parametrized Kantorovich-Rubinstein theorem and application to the coupling of random variables
... To prove (3), Berbee built a couple (X, X ∗ ) whose conditional distribution given M is the random probability λ ω defined by (2), with random margins µ = P X|M and ν = P X . It is by now well known that ...
16
Ascending runs in dependent uniformly distributed random variables: Application to wireless networks
... Abstract: We analyze in this paper the longest increasing contiguous sequence or maximal ascending run of random variables with common uniform distribution but not independent. Their dependence is ...
16
Ascending runs in dependent uniformly distributed random variables : Application to wireless networks
... Indeed, self-organization protocols relying on a coloring process achieve better stabilization time when the expected length of maximal ascending run is short but a coloring process stab[r] ...
15
Identification of random variables via Markov Chain Monte Carlo: benefits on reliability analysis
... the random variable for a further failure probability analysis, the compari- son between the true probability density function of the random variable k( ω) and the generated pre- dictive one has been ...
3