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In this paper we present uniform and nonuniform rates of convergence d sums of independent random variables to a stable law. The results obtained extend to the case of nonidentically distributed ra...
We prove some results concerning the almost sure approximation 01 contractions in L, by projections, unitary operators or partial isometries. In particular, a unitary operator for which no subseque...
For partial sums {S,) of a stationary ergodic sequence {X,} with zero mean we find conditions for m ny-'Pr {sup (S Jk) > E ] < m n= 1 k?n in terms of the strong mixing weficients {a,,) and moment...
We study the almost sure convergence of weighted averages of associated and negatively associated random variables. Our theorems extend and generalize strong laws of large numbers for positively an...
We obtain an almost sure convergence limit theorem for independent nonidentically distributed random variablcs. Lct S,, n 2 1, be the partial sums of independent random variables with zero means an...
This paper focuses on pconvolutions, a class of generalized convolutions of random vectors. It establishes the rate of convergence in uniform (Kolmogorov) metric for normalized n-fold p-convolution ...
The rate of convergence of penalized maximum likelihood estimation will be developd based on HeIlinger entropy with bracketing which measures the size of underlying spaces.
Let F be a non-lattice distribution function which lies in the domain of attraction of a normal distribution. Exact uniform convergence rates are obtained for the convergence of the normalized parti...
We investigate stability, with respect to convergence of coefficients, of one-dimensional It6 diRussions as well as one-dimensionat diffusions wrresponding to second order divergence form operators....
Several connections between the weak convergence of random variables, convergence of their distributions and conditioning have been described.
We prove the Marcinkiewicz-Zygmund SLLN (MZ- -SLLN) of order p, ~ € 1 12,[ , br associated sequences, not necessarily stationary. Our assumption on the moment of the random variables is minimal. We...

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