On the sequence of Bayesian estimates of normal random walk process

Jun S. Huang and Mark C. K. Yang

Stochastic Processes and their Applications, 1984, vol. 17, issue 1, 177-181

Abstract: Let ([mu]t)[infinity]t=0 be a k-variate (k[greater-or-equal, slanted]1) normal random walk process with successive increments being independently distributed as normal N([delta], R), and [mu]0 being distributed as normal N(0, V0). Let Xt have normal distribution N([mu]t, [Sigma]) when [mu]t is given, t = 1, 2,....Then the conditional distribution of [mu]t given X1, X2,..., Xt is shown to be normal N(Ut, Vt) where Ut's and Vt's satisfy some recursive relations. It is found that there exists a positive definite matrix V and a constant [theta], 0

Keywords: Bayesian; estimate; normal; random; walk; process; multivariate; normal; distribution (search for similar items in EconPapers)
Date: 1984
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