Difference between revisions of "Parameter estimation"
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In [[Bayesian Probability]], the parameters are estimated from data by computing the joint [[posterior distribution]] of the parameters and the data using [[Bayes Rule]]. | In [[Bayesian Probability]], the parameters are estimated from data by computing the joint [[posterior distribution]] of the parameters and the data using [[Bayes Rule]]. | ||
| − | [[category:Probability]] | + | [[category:Probability and Statistics]] |
Revision as of 21:16, November 8, 2009
In probability, once a model class has been selected it is then necessary to estimate the values of its associated parameters in order to specify that particular model out of all members of the model class which differ only on the basis of the values of these parameters.
In Bayesian Probability, the parameters are estimated from data by computing the joint posterior distribution of the parameters and the data using Bayes Rule.