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- ...Segmenting time series: A survey and novel approach]." Data mining in time series databases 57 (2004): 1-22.</ref> Probabilistic methods based on [[hidden Ma ...of time, the second approach generally takes into account the entire time-series when deciding which label to assign to a given point. ...5 KB (739 words) - 21:52, 12 June 2024
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- *[[Fourier series]] **[[Fourier–Bessel series]] ...2 KB (293 words) - 12:51, 21 February 2023
- {{Short description|Time series statistical test}} ...(or '''DF-GLS test''') is a test for a [[unit root]] in an economic [[time series]] sample. It was developed by Elliott, Rothenberg and Stock (ERS) in 1992 a ...3 KB (527 words) - 01:12, 30 March 2022
- ...the amplitude can be contoured on the frequency-time plane. This frequency-time distribution of the amplitude is designated as the Hilbert amplitude spectr ...er, "''Discrete-Time Signal Processing''," Prentice-Hall Signal Processing Series, 2 ed., 1999. ...1 KB (186 words) - 14:00, 7 January 2025
- ...iables produced by multiple individuals (the first dimension), in multiple series (the second dimension) at multiple times periods (the third dimension) and ...' is the individual dimension, ''s'' is the series dimension, ''t'' is the time dimension, and ''h'' is the horizon dimension. A general multidimensional p ...3 KB (434 words) - 15:50, 9 December 2016
- ...[[algorithm]] which factorizes a [[wikt:multivariate|multivariate]] [[time series]] into [[Stationary process|stationary]] and [[non-stationary]] components. ...tion of the stationary from the non-stationary sources in an observed time series. ...4 KB (553 words) - 21:34, 20 December 2021
- * <math display="inline">\mu_s</math> is the mean of the simulated time series (e.g.: flows predicted by the model) * <math display="inline">\mu_o</math> is the mean of the observed time series ...2 KB (340 words) - 13:23, 7 November 2024
- ...Segmenting time series: A survey and novel approach]." Data mining in time series databases 57 (2004): 1-22.</ref> Probabilistic methods based on [[hidden Ma ...of time, the second approach generally takes into account the entire time-series when deciding which label to assign to a given point. ...5 KB (739 words) - 21:52, 12 June 2024
- ...val ''T'') and/or periodic summation (at interval ''P'') of the underlying time-domain function.]] ...periodic summation''' of <math>S(f),</math> which is known as a [[discrete-time Fourier transform]]. ...3 KB (389 words) - 21:39, 16 February 2023
- ...ed in [[time series]] analysis to test the [[null hypothesis]] that a time series is [[order of integration|integrated of order]] 1. It builds on the [[Dick ...2 KB (298 words) - 01:12, 30 March 2022
- ...a function of the discrete variable, i.e. a discrete sequence. A Fourier series, by nature, has a discrete set of components with a discrete set of coeffic === Relation to Fourier series === ...4 KB (657 words) - 19:30, 14 December 2024
- ...The Advanced Theory of Statistics, Volume 3: Design and Analysis, and Time-Series | edition = 2nd | location = London | publisher = Griffin | isbn = 0-85264 ...''. The number of turning points is the number of maxima and minima in the series.<ref name="davison"/> ...4 KB (606 words) - 05:44, 27 June 2024
- ...ysis of the [[cross-correlation]] or [[cross-covariance]] between two time series. [[Category:Multivariate time series]] ...3 KB (376 words) - 10:05, 4 July 2022
- === Time Series Models === * '''Nonlinear Time Series Models''': In nonlinear time series models, stochastic equicontinuity ensures the stability and consistency of ...6 KB (770 words) - 08:54, 31 August 2024
- ...ual value at time ''t'' and ''F''<sub>''t''</sub> is the forecast value at time ''t''. Variable ''N'' represents number of forecasting points. The function ...How costly is it to ignore breaks when forecasting the direction of a time series?. International Journal of Forecasting, 20(3), 411-425 [https://www.reposit ...3 KB (465 words) - 18:11, 29 November 2024
- ...r '''σ-field of τ-past''') is a [[σ-algebra]] associated with a [[stopping time]] in the theory of [[stochastic process]]es, a branch of [[probability theo Let <math> \tau </math> be a [[stopping time]] on the [[filtered probability space]] <math> (\Omega, \mathcal A, (\mathc ...2 KB (366 words) - 17:10, 7 September 2024
- ...etric (mathematics)|metric]]. Its [[computational complexity|computational time complexity]] is <math>O(n^2)</math>, but can be drastically reduced in some TWED is also implemented into the Time Series Subsequence Search Python package (TSSEARCH for short) available at [https: ...11 KB (1,600 words) - 01:46, 17 May 2024
- == Non seasonal time series == For a non-seasonal time series,<ref name=":0"/> the mean absolute scaled error is estimated by ...8 KB (1,257 words) - 21:13, 21 December 2024
- ...r or nonlinear, and it can result from systematic changes in the data over time. A cyclostationary process can be formed by removing the trend component. T ...|first6=Sirak |last7=Hovhannisyan |first7=Narek |title=An Enterprise Time Series Forecasting System for Cloud Applications Using Transfer Learning |journal= ...7 KB (958 words) - 01:48, 23 December 2024
- {{Short description|Time series model}} ...hor=Shumway, Robert H. |url=http://worldcat.org/oclc/966563984 |title=Time series analysis and its applications : with R examples |last2=Stoffer |first2=Davi ...8 KB (1,136 words) - 16:00, 5 May 2024
- ...he coefficients are referred to as '''Wiener kernels'''. The terms of the series are orthogonal (uncorrelated) with respect to a statistical input of [[whit ...the output to the entire history of system input at any time. The Wiener series has been applied mostly to the identification of biological systems, especi ...5 KB (801 words) - 22:45, 11 July 2024