# time series

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Related to Univariate time series: Multivariate time series

## 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 ?
The MTS X has m variables and the corresponding component of the jth variable [x.sub.j] is a univariate time series of length n:
Each MTS dimension series is considered as a separate univariate time series. Firstly, similarity searching approach is used to search the similarity sequence for each dimension series; then the similar sequences of each dimensional series are synthesized on the weighted BORDA voting method to generate the multivariate similar sequences.
In order to evaluate forecasting performance of ANNs, we consider three univariate time series models.
Repeating the analysis in Section VA using this parsimonious multivariate time series model (as opposed to a univariate time series model), it is found that no breaks occur for any of the four series (FS, NFS, FH, and NFH).
Univariate time series analysis of the N[O.sub.3]-N and dissolved reactive P concentration data from Site 3 and Site 4 was also conducted.
The econometric method first examines the stationarity properties of the univariate time series. The present study uses the Augmented Dickey-Fuller (ADF) unit root test to examine the stationarity of the data series.
acf The module acf plots the sample autocorrelation function of a univariate time series. In assessing the adequacy of a fitted model, acf may be used to test whether the time series of residuals show significant autocorrelations.
In doing so, we used the bivariate autoregressive methodology recently proposed by King and Watson (1997), paying explicit attention to the univariate time series properties of the variables.
We consider first a simple class of univariate time series models of the `AR(p) + Trend(q)' form
Dennis and Taper (1994) reviewed many of the statistical and conceptual problems associated with the detection of density dependence in single populations, and proposed statistical methods for analyzing univariate time series data with a stochastic model of density-dependent population growth.
Univariate time series models are used, either explicitly or implicitly, to forecast the expected bond default risk premium.
Univariate Time Series Model of Quarterly Accounting Earnings per Share: A Proposed Model, Journal of Accounting Research, (Spring): 179-189.

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