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Weak convergence of random sums of infima of independent random variables。
Convergence rates in the strong law of large numbers for sums of random variables with multidimensional indices。
The paper proves theorems of [6] which are given here in a more general form. Moreover, some applications of the introduced version of the Anscornbe condition are discussed.
We give tbe rate of convergence in the central limit theorem and the random central limit theorem for functions belonging to the class I of all real differentiable functions g such that gr E L(1).
It is shown that every random closed set X in Rd, taking its realizations in the extended convex ring, is (up to equivalence) the union set of a po'int process Y of convex particles with the same i...
Probabilities of moderate deviations for randomly indexed sums of independent and identically dmtributed random variables with multidimensional indices are studied. The results presented extend som...
Tightness criteria for random measures with application to the principle of conditioning in Hilbert spaces。
Sequential estimation in random fields。
The Levy and the Dudley metrics are used to give estimates of the rate convergence in the centrat- limit theorem for some functions of the average of independent random variables.
Topology of the convergence in probability on a linear span of a sequence of independent random variables。
Random measure of non-compactness in PM-spaces and applications。
Weak convergence to the Brownian motion of the partial sums of infima of independent random variables。

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