kernel density estimator

kernel density estimator: French\ \ estimateur de densité de grain

German\ \ Kerndichteschätzer

Dutch\ \ schatter van de kerndichtheid

Italian\ \ estimatore di densità del nocciolo

Spanish\ \ perito de la densidad del núcleo

Catalan\ \ estimador d'una funció de densitat per nuclis

Portuguese\ \ estimador de densidade pelo método do núcleo

Romanian\ \ -

Danish\ \ -

Norwegian\ \ -

Swedish\ \ kärnestimator

Greek\ \ εκτιμητής πυκνότητας πυρήνων

Finnish\ \ ydinestimaattori

Hungarian\ \ -

Turkish\ \ çekirdek yoğunluk tahminleyicisi

Estonian\ \ -

Lithuanian\ \ -

Slovenian\ \ -

Polish\ \ -

Russian\ \ оценка плотности ядра

Ukrainian\ \ -

Serbian\ \ -

Icelandic\ \ kernel þéttleiki metilsins

Euskara\ \ nukleoaren dentsitatea zenbatesle

Farsi\ \ -

Persian-Farsi\ \ برآوردگر هسته‌ای

Arabic\ \ مقدر كثافة كرنل

Afrikaans\ \ kerndigtheidsberamer

Chinese\ \ -

Korean\ \ 핵밀도추정량

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Kernel density estimation — of 100 normally distributed random numbers using different smoothing bandwidths. In statistics, kernel density estimation is a non parametric way of estimating the probability density function of a random variable. Kernel density estimation is a… … Wikipedia
Multivariate kernel density estimation — Kernel density estimation is a nonparametric technique for density estimation i.e., estimation of probability density functions, which is one of the fundamental questions in statistics. It can be viewed as a generalisation of histogram density… … Wikipedia
Kernel regression — Not to be confused with Kernel principal component analysis. The kernel regression is a non parametric technique in statistics to estimate the conditional expectation of a random variable. The objective is to find a non linear relation between a… … Wikipedia
Density estimation — In probability and statistics, density estimation is the construction of an estimate, based on observed data, of an unobservable underlying probability density function. The unobservable density function is thought of as the density according to… … Wikipedia
Mean squared error — In statistics, the mean squared error (MSE) of an estimator is one of many ways to quantify the difference between values implied by a kernel density estimator and the true values of the quantity being estimated. MSE is a risk function,… … Wikipedia
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Outline of statistics — The following outline is provided as an overview and guide to the variety of topics included within the subject of statistics: Statistics pertains to the collection, analysis, interpretation, and presentation of data. It is applicable to a wide… … Wikipedia
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Local convex hull — (LoCoH) is a method for estimating the size the home range of an animal or a group of animals (e.g. a pack of wolves, a pride of lions, or herd of buffalos), and for constructing a utilization distribution. [Getz, W. M. and C. C. Wilmers, 2004. A … Wikipedia
Mode (statistics) — In statistics, the mode is the value that occurs most frequently in a data set or a probability distribution.[1] In some fields, notably education, sample data are often called scores, and the sample mode is known as the modal score.[2] Like the… … Wikipedia
k-nearest neighbor algorithm — KNN redirects here. For other uses, see KNN (disambiguation). In pattern recognition, the k nearest neighbor algorithm (k NN) is a method for classifying objects based on closest training examples in the feature space. k NN is a type of instance… … Wikipedia

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kernel density estimator

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