id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
work_mdzgknx6ynhuzdz3s2w4uhizyi	Prasanta S. Bandyopadhayay	The Curve Fitting Problem: A Bayesian Approach	1996	10	.pdf	application/pdf	5417	539	64	probability of the evidence given the hypothesis and is called the likelihood function. In our proposal, prior probability measures the simplicity of a hypothesis. Given prior probability and likelihood function of a hypothesis, we get its posterior probability. Bayesians can assign any prior probability to a hypothesis, provided that the In our account, simplicity of a theory determines its prior probability. One criticism of the proposed approach is that it appears to assign prior probability 1 to the maximum likelihood estimator, ai. new data fit well with a complex hypothesis H2, then it has better predictive accuracy and so has an evidential role to play. In both the cases, for pragmatists, simplicity of a theory has nothing to do with its predictive accuracy and therefore, has no evidential role to play the linear hypothesis is not an empirically adequate theory, since it does not provide a predictively accurate account of the relation between the response variable 	./cache/work_mdzgknx6ynhuzdz3s2w4uhizyi.pdf	./txt/work_mdzgknx6ynhuzdz3s2w4uhizyi.txt