A set of measures of behavior over time.

A time series is a set of ordered observations on a quantitative characteristic of an individual or collective phenomenon taken at different points of time. Although it is not essential, it is common for these points to be equidistant in time. The essential quality of the series is the order of the observations according to the time variable, as distinct from those which are not ordered at all or are ordered according to their internal properties; i.e, a set arranged in order of magnitude.

Discrete-time sequence of observations of a random process. The type of time series of interest in the GARCH Toolbox is typically a series of returns, or relative changes of some underlying price series.

Any sequence of measurements taken on a variable process over time. Usually illustrated as a graph whose vertical co-ordinate gives a value of the random response plotted against time on the horizontal axis.

A set of figures showing the magnitude of a given variable at regular points in time.

A set of measurements of something, usually at regular time intervals, in numerical form.

a series of values of a variable at successive times

a collection of observations made sequentially in time

a data set showing the state of a system over a period of time--a sequence of voting results, for instance, or the fluctuating price of gold

a data set that varies through time (e

a data set where each data element s k is associated with a time element t k

a geometrical progression-and there is ample theoretical and empirical data that it is-and the marginal increments have a Pareto-Levy stable frequency distribution

a group of sequential observations of a variable, produced by a random process

a line of variable values collected under a period of time, usually at even intervals

a list of repeated observations of a phenomenon, such as demand, arranged in the order in which they actually occurred

a random function x t of an argument t in a set T

a sequence of equally-spaced measures on some variable, e

a sequence of events/observations which are ordered in one dimension- time

a sequence of measuments made at regular times, for example, daily temperature at noon, monthly earnings, number of babies born each year in Chicago

a sequence of measurements over equal periods of time, such as days, months, or years

a sequence of measurements, typically taken at successive points in time

a sequence of measurements, usually taken at regular time intervals

a sequence of observations of a particular variable over time (e

a sequence of observations taken sequentially

a sequence of observation s which are order ed in time (or space)

a sequence of real numbers collected regularly in time, where each number represents a value

a sequence of time-ordered data values that are measurements of some physical processes

a sequence of values for specific fields recorded at regular intervals

a series of numbers indexed by time

a series of observations taken sequentially over time

a set of data collected at successive points in time or over successive periods of time

a set of data points recorded over successive time periods

a set of (dependent) observations recorded over some period of time

a set of numbers that measures the status of some activity over time

a set of observations recorded at successive points in time, normally at regular intervals

a set of values of some business or economic variable, measured at successive (usually equal) intervals of time

a set of values that have been recorded over a period of time which can then be represented using a Time Plot

a special case of a bivariate data-set in which the independent (x) variable is time

a temporally ordered collection of data with a distinct beginning and end (compare stream )

A set of values of a given element that is taken at different times as specified by a single time interval. A time series is implemented through the transfer set mechanism as defined within this specification.

A collection of data points indexed by time. CSI financial market data are indexed by trading day, but other economic time series are often indexed by week, month, quarter or year.

Data collected on the same population, in a comparative way, at regular intervals during a given period. Overall variations in the characteristics of a given population are observed over time. Statistics institutes and statistical teams are the main sources of time series data. Related Terms: Longitudinal data BACK

A set of data which shows how the value of a variable changes over time.

Problems (usually regression) where the objective is to predict later values of a variable or variables from earlier values.

a sequence of data assigned specific moments in time. It is the history of the object of interest

is an ordered sequence of values of a variable at equally spaced time intervals.

A collection of ordered pairs (t, X(t)), where t = time and X(t) = concentration (or activity) of a particular chemical species in the reaction network being modeled. This is the typical output from a simulation run. If the experimental data is also obtained as time series of species concentrations (or activities), then the comparison of simulations to experiments is straightforward. In many circumstances, however, the experimental data are some indirect measure of the effects of these time-varying chemicals, e.g., the percentage of cells in an asynchronous population that are in G1 phase of the cell cycle.

Any series of measurements of anything at all that are usually taken at regular intervals. Sometimes the intervals are not strictly regular such as calendar months, which are near enough for most purposes, or trading days which have weekends and public holidays missing which may cause some problems.

A sample of data values collected at equally spaced points in time. Possible autocorrelation between adjacent values makes it necessary to use special statistical methods to analyze this type of data.

A series of figures referring to different times, to show variation in magnitude of the particular item or items being measured. Definition of items measured must remain constant.

A variable in which the values are successive observations over time.

A set of ordered observations on a quantitative characteristic of an individual or collective phenomenon taken at different points in time. Usually the observations are successive and equally spaced in time.

A sequence of values generated from a dynamical system over time.

The values of a variable generated successively in time. A continuous barograph trace is an example of a continuous time series, while a sequence of hourly pressures is an example of a discrete time series. Graphically, a time series is usually plotted with time as the abscissa and the values of the function as the ordinate. Time series may be either stationary or nonstationary. For stationary time series the actual dynamics that motivate the series are constant from one period to the next. For nonstationary time series the dynamics are continually changing and such series are less susceptible to statistical analysis. Wadsworth, G. P., 1951: Compendium of Meteorology, 849–855.

Any series of observations of a physical variable that is sampled at changing time intervals. A regular sampling interval is usually presumed although not required.

A set of data that is distributed over time, such as demand data in monthly time periods. Various patterns of demand must be considered in time series analysis: seasonal, trend, cyclical, and random.

A series of measurements taken at consecutive points in time. Data mining products which handle time series incorporate time-related operators such as moving average. (Also see windowing.)

In statistics and signal processing, a time series is a sequence of data points, measured typically at successive times, spaced at (often uniform) time intervals. Time series analysis comprises methods that attempt to understand such time series, often either to understand the underlying theory of the data points (where did they come from? what generated them?), or to make forecasts (predictions). Time series prediction is the use of a model to predict future events based on known past events: to predict future data points before they are measured.