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Big data problems present great challenges to statisti-cal analyses, especially from the computational side. In this paper, we consider regression estimation of high-order mo-ments in big data problem...
An efficient estimator is constructed for the quadratic covariation or integrated covolatility matrix of a multivariate continuous martingale based on noisy and non-synchronous observations under high...
This article derives the first two moments of the two versions of the Riesz distribution in the terms of their characteristic functions.
We present formulas for the (raw and central) moments and absolute moments of the normal distribution. We note that these results are not new, yet many textbooks miss out on at least some of them. Hen...
A brief presentation of basics of the theory of Tchebycheff and Markov systems of functions and its applications to extremal problems for integrals of such functions is given.
We study the minimal sample size N=N(n) that suffices to estimate the covariance matrix of an n-dimensional distribution by the sample covariance matrix in the operator norm, and with an arbitrary fix...
Recently, Serfling and Xiao (2007) extended the L-moment theory (Hosking, 1990) to the multivariate setting.
Let X1,X2, . . . ,Xn be independent and identically distributed random variables. We present an analytic method for computing the moments of Sn = Pn i=1 Xi. The method is illustrated with a simple...
We show how to compute lower bounds for the maximum possible Bayes error if the class-conditional distributions must satisfy moment constraints. Our approach makes use of Curto and Fialkow’s solution...
This paper introduces a new parsimonious structure for mixture of autoregressive models. The weighting coefficients are determined through latent random variables, following a hidden Markov model. ...
Exact lower bounds on the exponential moments of min(y,X) and X I {X < y} are provided given the first two moments of a random variable X. These bounds are useful in work on large deviations probabi...
Integral expressions for positive-part moments EXp + (p > 0) of random variables X are presented, in terms of the Fourier-Laplace or Fourier transforms of the distribution of X. A necessary and suff...
There are established basic inequalities for moments of generalized convolutions of probability measures. Moreover, some necessary and sufficient conditions for the existence of moments of the char...
We propose the Bayesian generalized method of moments(GMM), which is particularly useful when likelihood-based methods are difficult.Byde- riving the moments and concatenating them together,we build...
Domains of attraction and moments      Domains  attraction  moments        2009/9/24
The limit behaviour of scalar modifications of powers of probability measures under a generalized convolution is considered. In particular, some necessary and sufTtcient wnditions in terms of momen...

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