A Stochastic Multiplicative Model in Assessment of Training Programs
A strong limit theorem for functions of continuous random variables and an extension of the Shannon-McMillan theorem.
A sufficient condition for the Carasso-Kato theorem.
A sufficient condition for the Carasso-Kato theorem (Erratum).
A survey on continuous elliptical vector distributions.
In this paper it is taken up a revision and characterization of the class of absolutely continuous elliptical distributions upon a parameterization based on the density function. Their properties (probabilistic characteristics, affine transformations, marginal and conditional distributions and regression) are shown in a practical and easy to interpret way. Two examples are fully undertaken: the multivariate double exponential distribution and the multivariate uniform distribution.
A survey on the general central limit problem in Banach spaces
A tail bound for sums of independent random variables and application to the Pareto distribution.
A tail inequality for suprema of unbounded empirical processes with applications to Markov chains.
A theorem on weak type estimates for Riesz transforms and martingale transforms
The Riesz transforms of a positive singular measure satisfy the weak type inequalitywhere denotes Lebesgue measure and is a positive constant only depending on .
A theoretical argument why the -copula explains credit risk contagion better than the Gaussian copula.
A unified approach to several inequalities for gaussian and diffusion measures
A Weak-Type Inequality for Orthogonal Submartingales and Subharmonic Functions
Let X be a submartingale starting from 0, and Y be a semimartingale which is orthogonal and strongly differentially subordinate to X. The paper contains the proof of the sharp estimate . As an application, a related weak-type inequality for smooth functions on Euclidean domains is established.
A weighted version of Gamma distribution
Weighted Gamma (WG), a weighted version of Gamma distribution, is introduced. The hazard function is increasing or upside-down bathtub depending upon the values of the parameters. This distribution can be obtained as a hidden upper truncation model. The expressions for the moment generating function and the moments are given. The non-linear equations for finding maximum likelihood estimators (MLEs) of parameters are provided and MLEs have been computed through simulations and also for a real data...
About projections of logarithmic Sobolev inequalities
About the density of spectral measure of the two-dimensional SaS random vector
In this paper, we consider a symmetric α-stable p-sub-stable two-dimensional random vector. Our purpose is to show when the function is a characteristic function of such a vector for some p and α. The solution of this problem we can find in [3], in the language of isometric embeddings of Banach spaces. Our proof is based on simple properties of stable distributions and some characterization given in [4].
About the generating function of a left bounded integer-valued random variable
We give a relation between the sign of the mean of an integer-valued, left bounded, random variable and the number of zeros of inside the unit disk, where is the generating function of , under some mild conditions
About the stationary states of vortex systems
Accuracy of approximation in the Poisson theorem in terms of the -distance.
Adaptive estimation of a quadratic functional of a density by model selection
We consider the problem of estimating the integral of the square of a density from the observation of a sample. Our method to estimate is based on model selection via some penalized criterion. We prove that our estimator achieves the adaptive rates established by Efroimovich and Low on classes of smooth functions. A key point of the proof is an exponential inequality for -statistics of order 2 due to Houdré and Reynaud.
Adaptive estimation of a quadratic functional of a density by model selection
We consider the problem of estimating the integral of the square of a density f from the observation of a n sample. Our method to estimate is based on model selection via some penalized criterion. We prove that our estimator achieves the adaptive rates established by Efroimovich and Low on classes of smooth functions. A key point of the proof is an exponential inequality for U-statistics of order 2 due to Houdré and Reynaud.