Stability Problems for Stochastic Models: Proceedings of the 9th International Seminar held in Varna, Bulgaria, May 13-19, 1985 - Softcover

9783662191804: Stability Problems for Stochastic Models: Proceedings of the 9th International Seminar held in Varna, Bulgaria, May 13-19, 1985

Softcover

ISBN 10: 3662191806 ISBN 13: 9783662191804

Publisher: Springer, 2014

This specific ISBN edition is currently not available.

The estimation of the rate of convergence in the integral limit theorem in the Euclidean motion group.- Contribution to the analytic theory of linear forms of independent random variables.- ?p-strictly stable laws and estimation of their parameters.- The method of metric distances in the problem of estimation of the deviation from the exponential distribution.- The accuracy of the normal approximation to the distribution of the sum of a random number of independent random variables.- Mixtures of probability distributions.- Some limit theorems for summability methods of I.I.D.Random variables.- Properties of mode of spectral positive stable distributions.- Two characterizations using records.- On orthogonal-series estimators for probability distributions.- Estimates of the deviation between the exponential and new classes of bivariate distributions.- On the difference between distributions of sums and maxima.- On the inequalities of Berry-Esseen and V.M. Zolotarev.- Some fixed point theorems probabilistic metric spaces.- The asymptotic bias in a deviation of a location model.- Cramer's decomposition theorem within the continuation of distribution functions.- An asymptotically most Bias-Robust invariant estimator of location.- Characterizing the distributions of the random vectors X 1, X 2, X 3 by the distribution of the statistic (X 1-X 3, X 2-X 3).- On stability estimates of Cramer's theorem.- On the estimation of moments of regenerative cycles in a general closed central-server queueing network.- On F-processes and their applications.- On some properties of ideal metrics of order ?.- On ?-independence of sample mean and sample variance.

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