Bayesian statistics


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Bayesian statistics

[¦bāz·ē·ən stə′tis·tiks]
(statistics)
An approach to statistics in which estimates are based on a synthesis of a prior distribution and current sample data.
References in periodicals archive ?
Most engineers find the philosophy of Bayesian statistics to be appealing and the associated techniques are often much more powerful than the corresponding classical ones.
In Bayesian statistics, the measurement data are given constants and the value of the measurand is a random variable.
Writing for students and graduates in food science and technology, Van Boekel (food science and technology, Wageningen University, The Netherlands) explains methods for modeling quality changes taking place in food as it is processed "from the farm to the fork," encompassing the fields of food science, kinetics, and Bayesian statistics.
His experience extends well beyond the estimation of risk using Bayesian statistics and focuses on identifying and managing sources of risk that stem from systematic forces and cognitive/behavioral biases that influence interactions between market participants," said Lee Partridge, Salient's Chief Investment Officer.
Brace yourself: It has something to do with Bayesian statistics.
The book describes basic concepts, bias, chance, causation, evidence-based medicine and its strengths and weaknesses, Bayesian statistics, and contextual topics like how journal articles get published, how research impacts practice, the influence of the pharmaceutical industry, and bioethics.
Irving John Good is a British statistician known for his works on Bayesian statistics who also worked as a wartime cryptographer under Alan Turing at Bletchley Park.
Recent work has demonstrated that Bayesian statistics can be used to remove reference sample bias and to obtain more reliable age estimates (Konigsberg & Frankenberg 1994; Lucy et al.
The author also discusses linear programming models and decision making under risk as well as less standard topics in the field such as game theory and Bayesian statistics.
It is marvelous to see his outstanding book awarded a prize named after Morrie DeGroot, the founder of the department and a major figure in the development of Bayesian statistics.
He includes survival analysis, bootstrapping, Bayesian statistics and sampling in a special section and provides solutions to selected exercises.