data-smoothing method
1Smoothing 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… …
2data compression — Process of reducing the amount of data needed for storage or transmission of a given piece of information (text, graphics, video, sound, etc.), typically by use of encoding techniques. Data compression is characterized as either lossy or lossless …
3Exponential smoothing — is a technique that can be applied to time series data, either to produce smoothed data for presentation, or to make forecasts. The time series data themselves are a sequence of observations. The observed phenomenon may be an essentially random… …
4maximum forward rate smoothing — An alternative yield curve smoothing technique. The most accurate yield curve smoothing method for forward rates. The yield curve with the smoothest possible forward rate function, consistent with observable data, is closely related to but… …
5Numerical 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… …
6Reassignment method — The method of reassignment is a technique forsharpening a time frequency representation by mappingthe data to time frequency coordinates that are nearer tothe true region of support of theanalyzed signal. The method has been… …
7Savitzky–Golay smoothing filter — The Savitzky–Golay smoothing filter is a type of filter first described in 1964 by Abraham Savitzky and Marcel J. E. Golay. [A. Savitzky and Marcel J.E. Golay (1964). Smoothing and Differentiation of Data by Simplified Least Squares Procedures .… …
8Multigrid method — Multigrid (MG) methods in numerical analysis are a group of algorithms for solving differential equations using a hierarchy of discretizations. They are an example of a class of techniques called multiresolution methods, very useful in (but not… …
9Kernel 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… …
10Hendrik Wade Bode — Infobox Scientist name = Hendrik Wade Bode image width = 162 caption = Hendrik Wade Bode birth date = birth date|1905|12|24|df=y death date = death date and age|1982|6|21|1905|12|24|df=y birth place = Madison, Wisconsin death place = Cambridge,… …
