Search results

...Le Cam convolution theorem''' states that any [[regular estimator]] in a [[parametric model]] is asymptotically equivalent to a sum of two [[independence (probab ...wn to always exist for [[parametric model#Regular parametric model|regular parametric model]]s. ...

In [[statistics]], '''Hoeffding's test of independence''', named after [[Wassily Hoeffding] .../www.jstor.org/stable/pdf/2237758.pdf|journal=[[The Annals of Mathematical Statistics]]|year=1961 |volume=32|pages=485–498|number=2|doi=10.1214/aoms/1177705055 | ...

...], an '''adaptive estimator''' is an [[estimator]] in a [[parametric model|parametric]] or [[semiparametric model|semiparametric]] model with [[nuisance paramete Formally, let parameter ''θ'' in a parametric model consists of two parts: the parameter of interest {{nowrap|''ν'' ∈ ''N ...

...equation, the Phillips–Perron test makes a [[non-parametric statistics|non-parametric]] correction to the t-test statistic. The test is robust with respect to un ...

...imation]].<ref>{{cite journal |last1=Epanechnikov |first1=V. A. |title=Non-Parametric Estimation of a Multivariate Probability Density |journal=Theory of Probabi ...eferred to as the Epanechnikov kernel. For more information, see [[Kernel (statistics)#Kernel functions in common use|Kernel functions in common use]]. ...

...article/10.1007/s00704-003-0026-3 |language=en |issn=1434-4483}}</ref> Non-parametric tests have the advantage of being more resistant to misbehaviour of the dat ...xactness''': A test can be [[exact test|exact]] or be [[Asymptotic theory (statistics)|asymptotic]] delivering approximate results. ...

...erval estimation]] by eliminating procedures based on [[Asymptotic theory (statistics)|asymptotic]] and approximate statistical methods. The main characteristic ...as higher-way ANOVA [[regression analysis]], and mixed models, only exact parametric methods are available. ...

...omputation of [[Mann–Whitney U|Mann–Whitney–Wilcoxon]] (MWW) rank-sum test statistics.<ref>{{Cite web |title=www.Ranklets.net |url=http://www.eecs.qmul.ac.uk/~fa | contribution = Ranklets: Orientation Selective Non-Parametric Features Applied to Face Detection ...

...://link.springer.com/book/10.1007/0-387-30623-4 |journal=Springer Texts in Statistics |language=en |doi=10.1007/0-387-30623-4|isbn=978-0-387-25145-5 }}</ref> ...ility density functions of several [[normal distributions]] (from the same parametric family).]] ...

...otic normality holds is in the case of [[i.i.d]] sampling from a [[regular parametric model]]. ...van der |url=http://dx.doi.org/10.1017/cbo9780511802256 |title=Asymptotic Statistics |date=1998-10-13 |publisher=Cambridge University Press |isbn=978-0-511-8022 ...

...hypothetical distribution function <math>F</math>, or a given hypothetical parametric family of distribution functions <math> \{ F_\theta : \theta \in \Theta \}< ...unctional (mathematics)|functional]]s of <math>v_n</math> are used as test statistics. The change of the variable <math>v_n(x)=u_n(t)</math>, <math>t=F(x)</math> ...

{{Short description|Non-parametric statistical test}} ...e<ref name="Clarke1993">{{cite journal|last1=Clarke|first1=K. R.|title=Non-parametric multivariate analyses of changes in community structure|journal=Austral Eco ...

In [[probability theory]], especially as it is used in [[statistics]], a '''group family''' of [[probability distribution]]s is one obtained by [[Category:Parametric statistics]] ...

...x}}</ref> is a [[non-parametric statistics|non-parametric]] [[multivariate statistics|multivariate]] statistical [[permutation test]]. PERMANOVA is used to compa ...

...=The definition of a statistical manifold |title=Differential Geometry and Statistics |publisher=Chapman & Hall |year=1993 |pages=76–77 |isbn=0-412-39860-5 |chap ...perbolic space]]. A way of picturing the manifold is done by inferring the parametric equations via the Fisher Information rather than starting from the likeliho ...

of disciplines, from bio-statistics to economics.<ref>{{Cite report|url=https://www.iser.essex.ac.uk/files/teac ...ne hazard functions. These specifications include fully [[Parametric model|parametric models]], piece-wise-constant proportional hazard models, or partial likeli ...

...c.org}}</ref> They are basic [[summary statistics]], used in [[descriptive statistics]] such as the [[five-number summary]] and [[seven-number summary#Bowley’s s The sample maximum and minimum are the ''least'' [[robust statistics]]: they are maximally sensitive to outliers. ...

In [[statistics]], the '''focused information criterion (FIC)''' is a method for selecting ...parametric]], [[semiparametric model|semiparametric]] and [[non-parametric statistics|nonparametric]] situations, involving separate estimation of squared bias a ...

In statistics, '''biweight midcorrelation''' (also called '''bicor''') is a [[Similarity ...tics: Raku module for doing statistics | url=https://github.com/sumanstats/Statistics|website=GitHub|accessdate=2022-03-11}}</ref> ...

...[probability]], the '''dependent Dirichlet process (DDP)''' provides a non-parametric [[prior probability distribution|prior]] over evolving [[mixture model]]s. [[Category:Nonparametric statistics]] ...