Difference between revisions of "Parameter estimation"
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(New page: In probability, once a distribution has been selected it is then necessary to estimate the values of its associated ''parameters'' in order to specify the particular distribution out of th...) |
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| − | In probability, once a | + | 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 [[parameter]]s. |
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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]]. | ||
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| + | [[Category:Probability and Statistics]] | ||
Latest revision as of 17:13, July 13, 2016
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.