Estimating parameters by frequentist and Bayesian approaches

Estimating parameters by frequentist and Bayesian approaches

Frequentists estimate parameters by choosing the value that maximises the likelihood of the data. The Bayesian approach assumes that the unknown value of a parameter is drawn from a prior distribution and it can be estimated by the mean of the distribution of the parameter conditional on the data. T...

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Bibliographische Detailangaben
Hauptverfasser: Goddard, Mike E., XIANG, RUIDONG, Almasi, Fazel
Format: Video
Sprache:eng
Schlagworte:
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Zusammenfassung:Frequentists estimate parameters by choosing the value that maximises the likelihood of the data. The Bayesian approach assumes that the unknown value of a parameter is drawn from a prior distribution and it can be estimated by the mean of the distribution of the parameter conditional on the data. The Bayesian approach is often superior if a rational prior distribution is known.Survey link: https://www.surveymonkey.com/r/Q3BJ72Y
DOI:10.26181/17055320