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A Bayesian Analysis of the Linear Calibration Problem

William G. Hunter, Warren F. Lamboy

Open publisher page 24 citations

Abstract

As part of a Bayesian analysis of the linear calibration problem, a posterior distribution is derived that is mathematically identical to the structural distribution obtained by Kalotay (1971) but different from the Bayesian distribution obtained by Hoadley (1970). Useful approximations are given. Although this posterior distribution has infinite variance, no practical problems arise in using it. The controversy concerning infinite variances and the use of inverse regression is discussed.

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What this paper is about

As part of a Bayesian analysis of the linear calibration problem, a posterior distribution is derived that is mathematically identical to the structural distribution obtained by Kalotay (1971) but different from the Bayesian distribution obtained by Hoadley (1970). Useful approximations are given. Although this posterior distribution has infinite variance, no practical problems arise in using it. The controversy concerning infinite variances and the use of inverse regression is discussed.

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OpenAlex reports 24 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

As part of a Bayesian analysis of the linear calibration problem, a posterior distribution is derived that is mathematically identical to the structural distribution obtained by Kalotay (1971) but different from the Bayesian distribution obtained by Hoadley (1970). Useful approximations are given. Although this posterior distribution has infinite variance, no practical problems arise in using it. The controversy concerning infinite variances and the use of inverse regression is discussed.

Key concepts: Bayesian probability, Calibration, Mathematics, Computer science, Econometrics, Statistics

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