- Bayesian loss
- Математика: байесовские потери
Универсальный англо-русский словарь. Академик.ру. 2011.
Универсальный англо-русский словарь. Академик.ру. 2011.
Bayesian inference — is statistical inference in which evidence or observations are used to update or to newly infer the probability that a hypothesis may be true. The name Bayesian comes from the frequent use of Bayes theorem in the inference process. Bayes theorem… … Wikipedia
Loss function — In statistics and decision theory a loss function is a function that maps an event onto a real number intuitively representing some cost associated with the event. Typically it is used for parameter estimation, and the event in question is some… … Wikipedia
Bayesian network — A Bayesian network, Bayes network, belief network or directed acyclic graphical model is a probabilistic graphical model that represents a set of random variables and their conditional dependencies via a directed acyclic graph (DAG). For example … Wikipedia
Prior probability — Bayesian statistics Theory Bayesian probability Probability interpretations Bayes theorem Bayes rule · Bayes factor Bayesian inference Bayesian network Prior · Posterior · Likelihood … Wikipedia
Statistical inference — In statistics, statistical inference is the process of drawing conclusions from data that are subject to random variation, for example, observational errors or sampling variation.[1] More substantially, the terms statistical inference,… … Wikipedia
Empirical Bayes method — In statistics, empirical Bayes methods are a class of methods which use empirical data to evaluate / approximate the conditional probability distributions that arise from Bayes theorem. These methods allow one to estimate quantities… … Wikipedia
Maximum a posteriori estimation — In Bayesian statistics, a maximum a posteriori probability (MAP) estimate is a mode of the posterior distribution. The MAP can be used to obtain a point estimate of an unobserved quantity on the basis of empirical data. It is closely related to… … Wikipedia
Admissible decision rule — In classical (frequentist) decision theory, an admissible decision rule is a rule for making a decision that is better than any other rule that may compete with it, in a specific sense defined below. Generally speaking, in most decision problems… … Wikipedia
Bayes estimator — In decision theory and estimation theory, a Bayes estimator is an estimator or decision rule that maximizes the posterior expected value of a utility function or minimizes the posterior expected value of a loss function (also called posterior… … Wikipedia
Effect size — In statistics, an effect size is a measure of the strength of the relationship between two variables in a statistical population, or a sample based estimate of that quantity. An effect size calculated from data is a descriptive statistic that… … Wikipedia
List of statistics topics — Please add any Wikipedia articles related to statistics that are not already on this list.The Related changes link in the margin of this page (below search) leads to a list of the most recent changes to the articles listed below. To see the most… … Wikipedia