bayesian criterion
81Invariant estimator — In statistics, the concept of being an invariant estimator is a criterion that can be used to compare the properties of different estimators for the same quantity. It is a way of formalising the idea that an estimator should have certain… …
82Minimax estimator — In statistical decision theory, where we are faced with the problem of estimating a deterministic parameter (vector) from observations an estimator (estimation rule) is called minimax if its maximal risk is minimal among all estimators of . In a… …
83Regression discontinuity design — In statistics, econometrics, epidemiology and related disciplines, a regression discontinuity design (RDD) is a design that elicits the causal effects of interventions by exploiting a given exogenous threshold determining assignment to treatment …
84Likelihood function — In statistics, a likelihood function (often simply the likelihood) is a function of the parameters of a statistical model, defined as follows: the likelihood of a set of parameter values given some observed outcomes is equal to the probability of …
85Expected utility hypothesis — In economics, game theory, and decision theory the expected utility hypothesis is a theory of utility in which betting preferences of people with regard to uncertain outcomes (gambles) are represented by a function of the payouts (whether in… …
86Informationskriterium — Ein Informationskriterium ist ein Kriterium zur Auswahl eines Modells in der angewandten Statistik bzw. der Ökonometrie. Dabei gehen die Anpassungsgüte des geschätzten Modells an die vorliegenden empirischen Daten (Stichprobe) und Komplexität des …
87Causality — (but not causation) denotes a necessary relationship between one event (called cause) and another event (called effect) which is the direct consequence (result) of the first. [http://dictionary.reference.com/search?q=Causality x=35 y=25 Random… …
88Non-linear least squares — is the form of least squares analysis which is used to fit a set of m observations with a model that is non linear in n unknown parameters (m > n). It is used in some forms of non linear regression. The basis of the method is to… …
89Aggregated Indices Randomization Method — (AIRM) is a modification of well known aggregated indices method being aimed at complex objects multi criteria estimation under uncertainty. The main advantage of AIRM over other variants of aggregated indices methods is its ability to use non… …
90Ordinary least squares — This article is about the statistical properties of unweighted linear regression analysis. For more general regression analysis, see regression analysis. For linear regression on a single variable, see simple linear regression. For the… …
