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Stability Problems for Stochastic Models [electronic resource] : Proceedings of the 9th International Seminar held in Varna, Bulgaria, May 13–19, 1985 / edited by Vladimir V. Kalashnikov, Boyan Penkov, Vladimir M. Zolotarev.

Contributor(s): Material type: TextTextSeries: Lecture Notes in Mathematics ; 1233Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 1987Description: VIII, 224 p. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783540473947
Subject(s): Additional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification:
  • 519.2 23
LOC classification:
  • QA273.A1-274.9
  • QA274-274.9
Online resources:
Contents:
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.
In: Springer eBooks
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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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