maximum-likelihood criterion
51Multiple comparisons — In statistics, the multiple comparisons or multiple testing problem occurs when one considers a set of statistical inferences simultaneously.[1] Errors in inference, including confidence intervals that fail to include their corresponding… …
52Linear discriminant analysis — (LDA) and the related Fisher s linear discriminant are methods used in statistics, pattern recognition and machine learning to find a linear combination of features which characterize or separate two or more classes of objects or events. The… …
53Neural modeling fields — Neural modeling field (NMF) is a mathematical framework for machine learning which combines ideas from neural networks, fuzzy logic, and model based recognition. It has also been referred to as modeling fields, modeling fields theory (MFT),… …
54Cladogram — For help on how to use cladograms in Wikipedia, see Help:Cladograms A horizontal cladogram, with the ancestor (not named) to the left …
55Bayesian experimental design — provides a general probability theoretical framework from which other theories on experimental design can be derived. It is based on Bayesian inference to interpret the observations/data acquired during the experiment. This allows accounting for… …
56Control chart — One of the Seven Basic Tools of Quality First described by Walter A. Shewhart …
57List of important publications in statistics — Probability Théorie analytique des probabilités :Author: Pierre Simon Laplace:Publication data: 1820 (3rd ed.):Online version: ?:Description: Attacks the roots of least squares and interpolation techniques, bringing back techniques from a century …
58Credible interval — Bayesian statistics Theory Bayesian probability Probability interpretations Bayes theorem Bayes rule · Bayes factor Bayesian inference Bayesian network Prior · Posterior · Likelihood …
59Logit-Modell — Logistische Funktion Unter logistischer Regression oder Logit Modell versteht man ein Verfahren zur (meist multivariaten) Analyse diskreter (z. B. binärer) abhängiger Variablen. Hierbei hat man Daten gegeben, wobei Yi einen binären …
60Logitmodell — Logistische Funktion Unter logistischer Regression oder Logit Modell versteht man ein Verfahren zur (meist multivariaten) Analyse diskreter (z. B. binärer) abhängiger Variablen. Hierbei hat man Daten gegeben, wobei Yi einen binären …
