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Abstract

Bayesian multivariate analysis is used in the solution of a pricing problem for a petrochemical product. Estimates of variables that determine optimal price are derived from subjective assessments and time series data. The two sets of estimates are combined using Bayesian posterior analysis, and expected losses are evaluated using Monte Carlo methods.

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References

Frederick

D. G.

and Laughhunn

D. J.

“A Note on the Subjective Specification of Covariance Matrices,” technical paper, University of Illinois, 1968.

Morrison

Donald F.

Multivariate Statistical Methods. New York: McGraw-Hill, 1967.

Naylor

Thomas

, et al. Computer Simulation Techniques. New York: John Wiley & Sons, 1966.

Pratt

John

, Raiffa

Howard

, and Schlaifer

Robert

. Introduction to Statistical Decision Theory, preliminary edition. New York: McGraw-Hill, 1965.

Raiffa

Howard

and Schlaifer

Robert

. Applied Statistical Decision Theory. Boston: Graduate School of Business Administration, Harvard University, 1961.

Schlaifer

Robert

. Probability and Statistics for Business Decisions. New York: McGraw-Hill, 1959.

An Industrial Pricing Decision Using Bayesian Multivariate Analysis

Abstract

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References