Limiting distributions of two random sequences
For fixed p (0 <= p <= 1), let {L0, R0} = {0, 1} and X1 be a uniform random variable over {L0, R0}. With probability p let {L1, R1} = {L0, X1} or = {X1, R0} according as ; with probability 1 - p let {L1, R1} = {X1, R0} or = {L0, X1} according as , and let X2 be a uniform random variable over {L1, R1}. For n >= 2, with probability p let {Ln, Rn} = {Ln - 1, Xn} or = {Xn, Rn - 1} according as , with probability 1 - p let {Ln, Rn} = {Xn, Rn - 1} or = {Ln - 1, Xn} according as , and let Xn + 1 be a uniform random variable over {Ln, Rn}. By this iterated procedure, a random sequence {Xn}n >= 1 is constructed, and it is easy to see that Xn converges to a random variable Yp (say) almost surely as n --> [infinity]. Then what is the distribution of Yp? It is shown that the Beta, (2, 2) distribution is the distribution of Y1; that is, the probability density function of Y1 is g(y) = 6y(1 - y) I0,1(y). It is also shown that the distribution of Y0 is not a known distribution but has some interesting properties (convexity and differentiability).
Year of publication: |
1984
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Authors: | Chen, Robert ; Goodman, Richard ; Zame, Alan |
Published in: |
Journal of Multivariate Analysis. - Elsevier, ISSN 0047-259X. - Vol. 14.1984, 2, p. 221-230
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Publisher: |
Elsevier |
Keywords: | Beta distribution uniform random variable convexity differentiability moment generating function confluent hypergeometric function characteristic function |
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