- smoothing estimation
- мат. сглаживающее оценивание
Большой англо-русский и русско-английский словарь. 2001.
Большой англо-русский и русско-английский словарь. 2001.
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 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
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
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
Exponential 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… … Wikipedia
List of digital estimation techniques — *Linear models **Parameter Estimation ***Deterministic parameters ****Least squares (batch and recursive processing) ****Best linear unbiased estimation (BLUE) ****Maximum likelihood ***Random parameters ****Mean squared ****Maximum a posteriori… … Wikipedia
Recursive Bayesian estimation — is a general probabilistic approach for estimating an unknown probability density function recursively over time using incoming measurements and a mathematical process model. Model The true state x is assumed to be an unobserved Markov process,… … Wikipedia
List of statistics topics — Please add any Wikipedia articles related to statistics that are not already on this list.The Related changes link in the margin of this page (below search) leads to a list of the most recent changes to the articles listed below. To see the most… … 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
Nonparametric regression — is a form of regression analysis in which the predictor does not take a predetermined form but is constructed according to information derived from the data. Nonparametric regression requires larger sample sizes than regression based on… … Wikipedia
Scale space — theory is a framework for multi scale signal representation developed by the computer vision, image processing and signal processing communities with complementary motivations from physics and biological vision. It is a formal theory for handling … Wikipedia