(Created page with "'''Jeffrey's Prior''' What is Jeffrey's Prior? Jeffrey's prior, a subset of Bayesian Statistics, is an objective prior distribution for a parameter space. A prior distributi...")
 
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Jeffrey's prior, a subset of Bayesian Statistics, is an objective prior distribution for a parameter space. A prior distribution is the probability distribution
 
Jeffrey's prior, a subset of Bayesian Statistics, is an objective prior distribution for a parameter space. A prior distribution is the probability distribution
that expresses ones belief about the distribution before some evidence is taken into account. The density function of Jeffrey's prior is proportional to the square root of the determinant of the Fisher's Information matrix. This can be shown as: p(/vector theta)
+
that expresses ones belief about the distribution before some evidence is taken into account. The density function of Jeffrey's prior is proportional to the square root of the determinant of the Fisher's Information matrix. This can be shown as: p(θ) \propto

Revision as of 21:12, 6 December 2020

Jeffrey's Prior

What is Jeffrey's Prior?

Jeffrey's prior, a subset of Bayesian Statistics, is an objective prior distribution for a parameter space. A prior distribution is the probability distribution that expresses ones belief about the distribution before some evidence is taken into account. The density function of Jeffrey's prior is proportional to the square root of the determinant of the Fisher's Information matrix. This can be shown as: p(θ) \propto

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