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Stochastic Processes

  • Textbook
  • © 1966

Overview

Authors:
  1. M. Girault

    1. University of Paris, France

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Part of the book series: Ökonometrie und Unternehmensforschung Econometrics and Operations Research (ÖKONOMETRIE, volume 3)

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Table of contents (6 chapters)

  1. Front Matter

    Pages I-XI
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  2. Introduction

    • M. Girault
    Pages 1-8

  3. Poisson processes

    • M. Girault
    Pages 8-31

  4. Numerical processes with independent random increments

    • M. Girault
    Pages 31-50

  5. Markov processes

    • M. Girault
    Pages 50-89

  6. Laplace processes and second order processes

    • M. Girault
    Pages 89-105

  7. Some Markov processes on continuous-time

    • M. Girault
    Pages 105-115

  8. Back Matter

    Pages 116-126
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Keywords

About this book

Existing works on stochastic processes belong to a field of abstract mathematics which puts them beyond the scope of the non-specialist. The preoccupations of research mathematicians being more often than not distant from the practical problems of experimental methodology, the needs of practical workers, though real, are not met by the majority of works that. deal with processes. By "practical workers", we mean research scientists in all the different disciplines: Physics, Chemistry, Biology, Medicine, Population, Economics, Organisation, Operational Research etc. Indeed, all scientific research today touches upon complex fields in which deterministic models can be useful for no more than an element­ ary and simple approximation. The Calculus of Probability although offering some interesting models is still inadequate in many instances, particularly in the study of evolving systems. The practical worker must therefore have at his disposal a set of original and varied stochastic models. These models must not be too general, for in that case not only would their theoretical study prove difficult, but above all the adaptation of such models to an observed system would lead to an estimation of a great number of parameters on the basis of a necessarily restricted sample. This would constitute an insuperable difficulty for the practical scientist. It is therefore essential for him to have at his disposal a varied range of very characteristic models.

Authors and Affiliations

  • University of Paris, France

    M. Girault

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