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autoregressive error

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  • Autoregressive moving average model — In statistics, autoregressive moving average (ARMA) models, sometimes called Box Jenkins models after the iterative Box Jenkins methodology usually used to estimate them, are typically applied to time series data.Given a time series of data X t …   Wikipedia

  • Autoregressive conditional heteroskedasticity — ARCH redirects here. For the children s rights organization, see Action on Rights for Children. In econometrics, AutoRegressive Conditional Heteroskedasticity (ARCH) models are used to characterize and model observed time series. They are used… …   Wikipedia

  • Autoregressive integrated moving average — In statistics, an autoregressive integrated moving average (ARIMA) model is a generalisation of an autoregressive moving average or (ARMA) model. These models are fitted to time series data either to better understand the data or to predict… …   Wikipedia

  • Autoregressive Conditional Heteroskedasticity - ARCH — An econometric term used for observed time series. ARCH models are used to model financial time series with time varying volatility, such as stock prices. The ARCH concept was developed by economist Robert F. Engle, for which he won the 2003… …   Investment dictionary

  • Nonlinear autoregressive exogenous model — In time series modeling, a nonlinear autoregressive exogenous model (NARX) is a nonlinear autoregressive model which has exogenous inputs. This means that the model relates the current value of a time series which one would like to explain or… …   Wikipedia

  • Generalized AutoRegressive Conditional Heteroskedasticity (GARCH) Process — An econometric term developed in 1982 by Robert F. Engle, an economist and 2003 winner of the Nobel Memorial Prize for Economics to describe an approach to estimate volatility in financial markets. There are several forms of GARCH modeling. The… …   Investment dictionary

  • 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

  • SETAR (model) — In statistics, Self Exciting Thereshold AutoRegressive (SETAR) models are typically applied to time series data as an extension of autoregressive models, in order to allow for higher degree of flexibility in model parameters through a regime… …   Wikipedia

  • STAR model — In statistics, Smooth Transition Autoregressive (STAR) models are typically applied to time series data as an extension of autoregressive models, in order to allow for higher degree of flexibility in model parameters through a smooth… …   Wikipedia

  • Durbin–Watson statistic — In statistics, the Durbin–Watson statistic is a test statistic used to detect the presence of autocorrelation (a relationship between values separated from each other by a given time lag) in the residuals (prediction errors) from a regression… …   Wikipedia

  • Moving-average model — In time series analysis, the moving average (MA) model is a common approach for modeling univariate time series models. The notation MA(q) refers to the moving average model of order q: where μ is the mean of the series, the θ1, ..., θq are the… …   Wikipedia

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