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The Akaike information criterion was formulated by the statistician Hirotugu Akaike. It was originally named "an information criterion". [ 22 ] It was first announced in English by Akaike at a 1971 symposium; the proceedings of the symposium were published in 1973.
In statistics, the Widely Applicable Information Criterion (WAIC), also known as Watanabe–Akaike information criterion, is the generalized version of the Akaike information criterion (AIC) onto singular statistical models. [1] It is used as measure how well will model predict data it wasn't trained on.
In statistics, the Bayesian information criterion (BIC) or Schwarz information criterion (also SIC, SBC, SBIC) is a criterion for model selection among a finite set of models; models with lower BIC are generally preferred. It is based, in part, on the likelihood function and it is closely related to the Akaike information criterion (AIC).
The Akaike information criterion (AIC) is an estimator of the relative quality of statistical models for a given set of data. Given a collection of models for the data, AIC estimates the quality of each model, relative to each of the other models. Thus, AIC provides a means for model selection.
Akaike information criterion; Deviance information criterion; Hosmer–Lemeshow test, a quality of fit statistic that can be used for binary data; Pearson's chi-squared test, an alternative quality of fit statistic for generalized linear models for count data; Peirce's criterion, a rule for eliminating outliers from data sets
From April 2012 to December 2012, if you bought shares in companies when William R. Loomis Jr. joined the board, and sold them when he left, you would have a 56.2 percent return on your investment, compared to a 2.8 percent return from the S&P 500.
Aggregate data; Aggregate pattern; Akaike information criterion; Algebra of random variables; Algebraic statistics; Algorithmic inference; Algorithms for calculating variance; All models are wrong; All-pairs testing; Allan variance; Alignments of random points; Almost surely; Alpha beta filter; Alternative hypothesis; Analyse-it – software ...
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