Stability problems for stochastic models : proceedings of the 6th international seminar, held in Moscow, USSR, April 1982
著者
書誌事項
Stability problems for stochastic models : proceedings of the 6th international seminar, held in Moscow, USSR, April 1982
（Lecture notes in mathematics, 982）
Springer-Verlag, 1983
- : Berlin
- : New York
大学図書館所蔵 全80件
注記
Organized by the Steklov Mathematical Institute of the Academy of Sciences of USSR, the International research Institute of Control Problems, and the Institute for Systems Studies
Includes bibliographical references
内容説明・目次
目次
Hypererlang approximation of probability distributions on (0, ?) and its application.- On the discrete analog of Marshall-Olkin's distribution.- On some stability theorems.- On stability estimation of certain characterization of the exponential distribution.- Accuracy estimation of the results of complex systems simulation with vector output and several types of randomnesses.- A complete metric in the function space D[0, ?) and its application.- On the estimation of location and scale parameters of stable laws.- Discretization in the problems of stability of characterization of the exponential distribution.- Some ouestions of stability theory of the stochastic economical models.- Characterizations of the bivariate exponential distribution and Marshall - Olkin distribution and stability.- On the growth of entire characteristic functions.- An elementary characterization of the multinomial and the multivariate hypergeometric distributions.- On the stability of characterizations of the unit distribution.- Minimal metrics in the real random variables space.- On poisson output of queueing systems.- On a relation between Levy - Prohorov metrics and ideal metrics.- On the stability of lack of memory characterization of the exponential distribution.- Several remarks on applications of one approach to studies of characterization problems of Polya's theorem type.- On the metrics of the type ?.- On a problem of Dugue.- Limit theorems in the problems of stability.- Robust statistical procedures: A general approach.
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