Advertisement

Introduction

  • M. Girault
Part of the Econometrics and Operations Research / Ökonometrie und Unternehmensforschung book series (ÖKONOMETRIE, volume 3)

Abstract

We denote by the name “Random Model” any abstract scheme of a probabilistic nature, which can represent certain real phenomena. As long as these models provide adequate representation of the phenomena under observation (in the same way as any mathematical model used by the engineer) they allow us to forecast the consequences of certain situations. Thus, these models afford the possibility of making calculated choices. For this reason, they play an important part in the science of decision, more so as their field of application is very wide, since they occur frequently.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    The classical Probability Theory is limited to the study of the three following cases: ∈ includes a finite number of states. ∈ is (real numbers). The model is called random variable. ∈ is the set Rk of vectors with k real components or random vectors. Of course, in order to study the law of large numbers, infinite sequences of random variables are considered but nevertheless the systematic study of Random infinite successions, is not undertaken.Google Scholar
  2. 1.
    The Borel set of R is the set obtained by making union or intersection of any denumerable sequence of generalized intervals.Google Scholar

Copyright information

© Springer-Verlag, Berlin · Heidelberg 1966

Authors and Affiliations

  • M. Girault
    • 1
  1. 1.University of ParisFrance

Personalised recommendations