In Bayesian statistics, a strong prior is a preceding assumption, theory, concept or idea upon which, after taking account of new information, a current assumption, theory, concept or idea is founded. The term is used to contrast the case of a weak or uniformative prior probability. A strong prior would be a type of informative prior in which the information contained in the prior distribution dominates the information contained in the data being analysed. The Bayesian analysis combines the information contained in the prior with that extracted from the data to produce the posterior distribution which, in the case of a "strong prior", would be little changed from the prior distribution.
Famous quotes containing the words strong and/or prior:
“You thought you could be Mrs. de Winter. Live in her house. Walk in her steps. Take the things that were hers. But she’s too strong for you. You can’t fight her. No one ever got the better of her. Never. Never. She was beaten in the end. But it wasn’t a man. It wasn’t a woman. It was the sea!”
—Robert E. Sherwood (1896–1955)
“A diff’rent cause, says Parson Sly,
The same effect may give:
Poor Lubin fears, that he shall die;
His wife, that he may live.”
—Matthew Prior (1664–1721)