Central Bank of Nigeria Library

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Stochastic Processes /

By: Material type: TextTextSeries: Holden-Day Series in Probability and Statistics edited by Lehman, E. LPublication details: San Francisco : Holden-Day, [1964, c1962].Description: 324 p.:illSubject(s): DDC classification:
  • 519.1 PAR
LOC classification:
  • QA273 .P278
Summary: The theory of Stochastic Processes is generally defined as the "dynamic" part of probability theory, in which one studies a collection of random variables (called stochastic process) from the point of view of their interdependence and limiting behavior. This course has three main aims: 1) to give examples of the wide variety of empirical phenomena for which stochastic processes provide mathematical models; 2) to provide an introduction to the methods of probability model-building; and 3) to provide the reader who does not possess an advanced mathematical background with mathematically sound techniques and with a sufficient degree of maturity to enable further study of the theory of stochastic processes.
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Holdings
Item type Current library Collection Call number Copy number Status Date due Barcode
Monograph & others Monograph & others CBN HQ Library General Stacks Non-fiction 519.1 PAR (Browse shelf(Opens below)) c.1 Available 31008100139373

Includes bibliographical references: p. [307]-313 and indexes: p. [3140-324.

The theory of Stochastic Processes is generally defined as the "dynamic" part of probability theory, in which one studies a collection of random variables (called stochastic process) from the point of view of their interdependence and limiting behavior. This course has three main aims: 1) to give examples of the wide variety of empirical phenomena for which stochastic processes provide mathematical models; 2) to provide an introduction to the methods of probability model-building; and 3) to provide the reader who does not possess an advanced mathematical background with mathematically sound techniques and with a sufficient degree of maturity to enable further study of the theory of stochastic processes.

ne 23/03/2018

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