What Are Time Series Models?
A time series is one or more measured output channels with no measured input. A time series model, also called a signal model, is a dynamic system that is identified to fit a given signal or time series data. The time series can be multivariate, which leads to multivariate models.
A time series is modeled by assuming it to be the output of a system that takes a white noise signal e(t) of variance λ as its virtual input. The true measured input size of such models is zero, and their governing equation takes the form:
y(t) = He(t)
Here, y(t) is the signal being modeled and H is the transfer function that represents the relationship between y(t) and e(t).
The multivariate power spectrum Φ of the time series y(t) is given by:
Φ = H(ΛTs)H'
Here Λ is the noise variance matrix and Ts is the model sample time.
System Identification Toolbox™ software provides tools for modeling and forecasting time-series data. You can estimate both linear and nonlinear black-box and grey-box models for time series data. A linear time series model can be a polynomial (idpoly
), state-space (idss
, or idgrey
) model. Some particular types of models are parametric autoregressive (AR), autoregressive and moving average (ARMA), and autoregressive models with integrated moving average (ARIMA). For nonlinear time series models, the toolbox supports nonlinear ARX models.
You can estimate time series spectra using both time- and frequency-domain data. Time-series spectra describe time series variations using cyclic components at different frequencies.
To represent a time series vector or a matrix s
as an iddata
object, use the following syntax:
y = iddata(s,[],Ts);
The following example illustrates a 4th order autoregressive model estimation for the time series data z9
that is stored in file iddata9
.
load iddata9 z9sys = ar(z9,4);
Because the model has no measured inputs, size(sys,2)
returns zero. The governing equation of sys
is A(q)y(t) = e(t). You can access the A polynomial using sys.A
and the estimated variance of the noise e(t) using sys.NoiseVariance
.
Related Topics
MATLAB Command
You clicked a link that corresponds to this MATLAB command:
Run the command by entering it in the MATLAB Command Window. Web browsers do not support MATLAB commands.
Select a Web Site
Choose a web site to get translated content where available and see local events and offers. Based on your location, we recommend that you select: .
You can also select a web site from the following list:
Americas
- América Latina (Español)
- Canada (English)
- United States (English)
Europe
- Belgium (English)
- Denmark (English)
- Deutschland (Deutsch)
- España (Español)
- Finland (English)
- France (Français)
- Ireland (English)
- Italia (Italiano)
- Luxembourg (English)
- Netherlands (English)
- Norway (English)
- Österreich (Deutsch)
- Portugal (English)
- Sweden (English)
- Switzerland
- United Kingdom (English)
Contact your local office