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searching for Likelihood principle 10 found (26 total)

Maximum likelihood estimation (9,609 words) [view diff] no match in snippet view article find links to article

In statistics, maximum likelihood estimation (MLE) is a method of estimating the parameters of an assumed probability distribution, given some observed

Sufficient statistic (6,668 words) [view diff] no match in snippet view article find links to article

In statistics, a statistic is sufficient with respect to a statistical model and its associated unknown parameter if "no other statistic that can be calculated

Multispectral imaging (2,674 words) [view diff] exact match in snippet view article find links to article

techniques include the maximum likelihood principle and convolutional neural network. The Maximum likelihood principle calculates the probability of a

Akaike information criterion (5,504 words) [view diff] exact match in snippet view article find links to article

H. (1973), "Information theory and an extension of the maximum likelihood principle", in Petrov, B. N.; Csáki, F. (eds.), 2nd International Symposium

James O. Berger (498 words) [view diff] case mismatch in snippet view article find links to article

ISBN 978-0-387-96098-2. Wolpert, Robert L.; Berger, James O. (1988). The Likelihood Principle. Institute of Mathematical Statistics. ISBN 978-0-940600-13-3. Wolpert

Confidence interval (4,617 words) [view diff] exact match in snippet view article find links to article

sample variance. Estimates can be constructed using the maximum likelihood principle, the likelihood theory for this provides two ways of constructing

Hirotugu Akaike (2,021 words) [view diff] exact match in snippet view article find links to article

H. (1973), "Information theory and an extension of the maximum likelihood principle", in Petrov, B. N.; Csáki, F. (eds.), 2nd International Symposium

Vidyadhar P. Godambe (570 words) [view diff] exact match in snippet view article find links to article

Journal of the Royal Statistical Society, he demonstrated that the likelihood principle implies that inference should be independent of the sampling design

Bayesian inference in marketing (3,125 words) [view diff] exact match in snippet view article find links to article

further complemented by the fact that Bayes inference satisfies the likelihood principle, which states that models or inferences for datasets leading to the

CMA-ES (7,543 words) [view diff] exact match in snippet view article find links to article

distribution are exploited in the CMA-ES algorithm. First, a maximum-likelihood principle, based on the idea to increase the probability of successful candidate