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...[[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. ...

{{short description|Specific multivariate linear model}} ...s, where multiple observations are made on collections of individuals over time.]] ...

...lication: In Press (1972)<ref>Press SJ (1972) Estimation in univariate and multivariate stable distributions. Journal of the American Statistical Association. 67:8 Since that time there has subsequently been a vast expansion of statistical inference metho ...

{{Short description|Family of distributions that generalize the multivariate normal distribution}} ...r of a broad family of [[probability distribution]]s that generalize the [[multivariate normal distribution]]. Intuitively, in the simplified two and three dimensi ...

...ysis of the [[cross-correlation]] or [[cross-covariance]] between two time series. [[Category:Multivariate time series]] ...

...l |doi=10.1016/S0019-9958(78)90275-9|title=Nonnegative entropy measures of multivariate symmetric correlations|year=1978|last1=Han|first1=Te Sun|journal=Informatio ...t2=Maria |last3=Faskowitz |first3=Joshua |last4=Sporns |first4=Olaf |title=Multivariate information theory uncovers synergistic subsystems of the human cerebral co ...

where <math>{}_{2}F_{1}</math> denotes the [[hypergeometric series]] (which converges for all ''h'' if ''c'' < 1, or for all ''h'' / ''a'' < ' ...to Distributions, Volume 5 in Statistical Distributions in Scientific Work Series, International Co-operative Publishing House, Burtonsville, Md. 1983.</ref> ...

== Multivariate Extensions == The multivariate generalization of the split normal distribution was proposed by Villani and ...

...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 ...

...[quantum computer]]. Multiple signature schemes have been devised based on multivariate equations with the goal of achieving [[Post-quantum cryptography|quantum re ...)|RSA]] the keys are both exponents. In the UOV scheme, and in every other multivariate signature scheme the keys are more complex. ...

...itle=Causality detection based on information-theoretic approaches in time series analysis|journal=Physics Reports|date=1 March 2007|volume=441|issue=1|pages ...|date=2012-05-15|title=Rényi's information transfer between financial time series|journal=Physica A: Statistical Mechanics and Its Applications|language=en|v ...

...rol Theory | series=Series on Stability, Vibration and Control of Systems, Series A | date=2001 | volume=6 | pages=155–166 | publisher=World Scientific | isb ...r |first3=Matthew C. |date=2023 |title=Aizerman Conjectures for a Class of Multivariate Positive Systems |url=https://ieeexplore.ieee.org/document/9931495 |journal ...

...| first3 = E. | year = 1999 | title = Cluster-weighted modelling for time-series analysis | journal = Nature | volume = 397 | issue = 6717| pages = 329–332 ...'',''x''). Here the "variables" might be uni-variate, multivariate or time-series. For convenience, any model parameters are not indicated in the notation he ...

...m''' is a formula that allows one to compute higher-order moments of the [[multivariate normal distribution]] in terms of its covariance matrix. It is named after ...of multivariate distribution parameters for non-Gaussian distributed time series ...

...te science for identifying representative patterns of variability in space-time data-sets such as historical climate observations,<ref name="jewson"/> [[En * a multivariate dataset of weather or climate data, such as historical climate observations ...

{{Distinguish|Discrete-time and continuous-time variables}} ...s |last5=Ramsay |first5=James O. |title=Parameter estimation in continuous-time dynamic models using principal differential analysis |journal=Computers & C ...

...th> are factor returns determined by a cross-sectional regression for each time period and <math>g(i,t)</math> are the regression residuals. This model was ...fic returns <math>e(i,t)</math> are fit by a weighted regression over each time period <math>t</math> for a representative asset universe. For instance the ...

[[File:oldfaithful3.png|thumb|240px|Waiting time between eruptions and the duration of the eruption for the [[Old Faithful G ...e=babbie/> Bivariate analysis is a simple (two variable) special case of [[multivariate analysis]] (where multiple relations between multiple variables are examine ...

The hafnian is also related to moments of [[multivariate Gaussian distribution]]s. ...rix composed of entries <math>z_j</math> (each one is presented twice, one time per nonzero block). Let <math>I</math> denote the [[identity matrix]]. Then ...

...e [[Latent and observable variables|unobservable]]s that are constant over time, such as motivation. [[Gary Chamberlain|Chamberlain]]'s approach to unobser ...with the [[linear projection]] of it onto the explanatory variables in all time periods. Specifically, this leads to the following equation ...