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Probability pp 339-392 | Cite as

Continuous Joint Distributions

  • Jim Pitman
Chapter

Abstract

The joint distribution of a pair of random variables X and Y is the probability distribution over the plane defined by
$$P\left( B \right) = P\left( {\left( {X,Y} \right) \in B} \right)$$
for subsets B of the plane. So P(B) is the probability that the random pair (X, Y) falls in the set B. Joint distributions for discrete random variables were considered in Section 3.1. This chapter shows how these ideas for discrete random variables are extended to two or more continuously distributed random variables with sums replaced by integrals.

Keywords

Joint Distribution Independent Random Variable Joint Density Normal Random Variable Rayleigh Distribution 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag New York, Inc. 1993

Authors and Affiliations

  • Jim Pitman
    • 1
  1. 1.Department of StatisticsUniversity of CaliforniaBerkeleyUSA

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