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An invariant form for the prior probability in estimation problems

Abstract

Abstract It is shown that a certain differential form depending on the values of the parameters in a law of chance is invariant for all transformations of the parameters when the law is differentiable with regard to all parameters. For laws containing a location and a scale parameter a form with a somewhat restricted type of invariance is found even when the law is not everywhere differentiable with regard to the parameters. This form has the properties required to give a general rule for stating the prior probability in a large class of estimation problems.

Advanced Statistical Methods and ModelsFinancial Risk and Volatility ModelingForecasting Techniques and ApplicationsDifferentiable functionMathematicsInvariant (physics)Scale invarianceApplied mathematicsClass (philosophy)EstimationMathematical analysisPure mathematicsStatistics

MeSH terms

BiometryHumansProbabilityRegression AnalysisStatistics as Topic
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