smoothing vector
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Smoothing spline — The smoothing spline is a method of smoothing, or fitting a smooth curve to a set of noisy observations.DefinitionLet (x i,Y i); i=1,dots,n be a sequence of observations, modeled by the relation E(Y i) = mu(x i). The smoothing spline estimate… … Wikipedia
Numerical smoothing and differentiation — An experimental datum value can be conceptually described as the sum of a signal and some noise, but in practice the two contributions cannot be separated. The purpose of smoothing is to increase the Signal to noise ratio without greatly… … Wikipedia
n-gram — Not to be confused with engram. In the fields of computational linguistics and probability, an n gram is a contiguous sequence of n items from a given sequence of text or speech. The items in question can be phonemes, syllables, letters, words or … Wikipedia
Linear least squares (mathematics) — This article is about the mathematics that underlie curve fitting using linear least squares. For statistical regression analysis using least squares, see linear regression. For linear regression on a single variable, see simple linear regression … Wikipedia
List of mathematics articles (S) — NOTOC S S duality S matrix S plane S transform S unit S.O.S. Mathematics SA subgroup Saccheri quadrilateral Sacks spiral Sacred geometry Saddle node bifurcation Saddle point Saddle surface Sadleirian Professor of Pure Mathematics Safe prime Safe… … Wikipedia
Kalman filter — Roles of the variables in the Kalman filter. (Larger image here) In statistics, the Kalman filter is a mathematical method named after Rudolf E. Kálmán. Its purpose is to use measurements observed over time, containing noise (random variations)… … 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
Good–Turing frequency estimation — is a statistical technique for predicting the probability of occurrence of objects belonging to an unknown number of species, given past observations of such objects and their species. (In drawing balls from an urn, the objects would be balls and … Wikipedia
Generalized linear array model — In statistics, the generalized linear array model(GLAM) is used for analyzing the data sets with array structure. It based on the generalized linear model with the regression matrix written as a Kronecker product. Overview In the article… … Wikipedia
Tethered particle motion — (TPM) is a biophysical method that is used for studying various polymers such as DNA and their interaction with other entities such as proteins. The method allows to measure various physical properties on the substances, as well as to measure the … Wikipedia
Linear least squares — is an important computational problem, that arises primarily in applications when it is desired to fit a linear mathematical model to measurements obtained from experiments. The goals of linear least squares are to extract predictions from the… … Wikipedia
