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Updating of moments

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  • Pötzelberger, Klaus

Abstract

Consider a statistical model, given by the distribution of the observation X, conditional on the parameter [theta], and the prior distribution of the parameter [theta]. Let Hx denote the function that maps the prior mean and the prior covariance matrix into the posterior mean and the posterior covariance matrix, when X = x is observed. We prove that if the conditional distribution of X belongs to an exponential family, then the function Hx characterizes the distribution of X[short parallel][theta].

Suggested Citation

  • Pötzelberger, Klaus, 1990. "Updating of moments," Journal of Multivariate Analysis, Elsevier, vol. 33(2), pages 220-229, May.
    • Handle: RePEc:eee:jmvana:v:33:y:1990:i:2:p:220-229
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