# time series

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## Time Series

A comparison of a variable to itself over time. One of the most common time series, especially in technical analysis, is a comparison of prices over time. For example, one may compile a time series of a security over the course of a week or a month or a year, and then use it in the determination of future price movements.

## time series

A set of variables with values related to the respective times the variables are measured. Thus, a weekly record of a stock's price throughout a period of years is a time series. Time series are often used to project future values by observing how the value of a variable has changed in the past.

## time series

any statistical information recorded over successive time periods. See TIME-SERIES ANALYSIS.
References in periodicals archive ?
Tsay summarizes the basic concepts and ideas of analyzing multivariate dependent data, provides econometric and statistical models useful for describing the dynamic dependence between variables, discusses the identifiability problem when the models become too flexible, introduces ways to search for simplifying structure hidden in high-dimensional time series, addresses the applicabilities and limitations of multivariate time series method, and develops a software package for readers to apply the methods and models he discusses.
Korobilis, 2009, "Bayesian Multivariate Time Series Methods for Empi-cal Macroeconomics," MPRA Paper, No.
A sampling of topics: stability conditions in contextual emergence, contextual emergence of mental states from neurodynamics, mutual phase synchronization in single trial data, ordinal analysis of EEG time series, quantification of order patterns recurrence plots of event related potentials, testing for coupling asymmetry using surrogate data, measuring the thalamocortical loop in patients, and assessment of connectivity patterns from multivariate time series by partial directed coherence.
Performance of alerts generated by individual monitoring of aggregate data and separate data streams, and simultaneous monitoring of multiple data streams by using univariate and multivariate time series models, Hong Kong, 1998-2007 * Univariate models Sensitivity Data AUWROC ([double dagger]) Aggregated data GP 0.
The third chapter extends the discussion to multivariate time series models represented by vector-autoregressive (VAR) and vector-autoregressive moving average (VARMA) models.

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