maximum probability estimator
- maximum probability estimator
French\ \ estimateur de probabilité maximale
German\ \ maximale Wahrscheinlichkeitsschätzung
Dutch\ \ maximale waarschijnlijkheidsschatter; maximale waarschijnlijkheidsschatter van Weiss-Wolfowitz
Italian\ \ stimatore di massima probabilità
Spanish\ \ estimador de máxima probabilidad
Catalan\ \ estimador de màxima probabilitat
Portuguese\ \ estimador da probabilidade máxima
Romanian\ \ -
Danish\ \ -
Norwegian\ \ -
Swedish\ \ -
Greek\ \ εκτιμητής μέγιστης πιθανότητας
Finnish\ \ suurimman todennäköisyyden estimaattori
Hungarian\ \ maximális valószínûségi becslés
Turkish\ \ en büyük olasılık tahminleyicisi
Estonian\ \ suurima tõenäosuse hinnangufunktsioon
Lithuanian\ \ didžiausiosios tikimybės įvertinys
Slovenian\ \ -
Polish\ \ estymator największego prawdopodobieństwa
Russian\ \ оценка максимальной вероятности
Ukrainian\ \ -
Serbian\ \ -
Icelandic\ \ hámarks líkur metilsins
Euskara\ \ gehienez probabilitatea zenbatesle
Farsi\ \ -
Persian-Farsi\ \ برآورد ماکسيمم احتمال
Arabic\ \ مقدر الاحتمال الاعظم
Afrikaans\ \ maksimumwaarskynlikheidsberamer
Chinese\ \ 最 大 概 率 估 计 量
Korean\ \ 최대확률추정량
Statistical terms.
2014.
Look at other dictionaries:
Maximum likelihood — In statistics, maximum likelihood estimation (MLE) is a method of estimating the parameters of a statistical model. When applied to a data set and given a statistical model, maximum likelihood estimation provides estimates for the model s… … Wikipedia
Maximum spacing estimation — The maximum spacing method tries to find a distribution function such that the spacings, D(i), are all approximately of the same length. This is done by maximizing their geometric mean. In statistics, maximum spacing estimation (MSE or MSP), or… … 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
Maximum parsimony — Maximum parsimony, often simply referred to as parsimony, is a non parametric statistical method commonly used in computational phylogenetics for estimating phylogenies. Under maximum parsimony, the preferred phylogenetic tree is the tree that… … Wikipedia
Estimator — In statistics, an estimator is a function of the observable sample data that is used to estimate an unknown population parameter (which is called the estimand ); an estimate is the result from the actual application of the function to a… … Wikipedia
Maximum parsimony (phylogenetics) — Parsimony is a non parametric statistical method commonly used in computational phylogenetics for estimating phylogenies. Under parsimony, the preferred phylogenetic tree is the tree that requires the least evolutionary change to explain some… … Wikipedia
Maximum a posteriori — In statistics, the method of maximum a posteriori (MAP, or posterior mode) estimation can be used to obtain a point estimate of an unobserved quantity on the basis of empirical data. It is closely related to Fisher s method of maximum likelihood… … Wikipedia
M-estimator — In statistics, M estimators are a broad class of statistics which are obtained as the solution to the problem of minimizing certain functions of the data. The process of obtaining an M estimator is called M estimation.Some authors define M… … 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
Bias of an estimator — In statistics, the difference between an estimator s expected value and the true value of the parameter being estimated is called the bias. An estimator or decision rule having nonzero bias is said to be biased.Although the term bias sounds… … Wikipedia
Minimax 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… … Wikipedia
