TimeSeriesModel
represents the symbolic time series model obtained from TimeSeriesModelFit.
Details and Options
- Properties of a time series model are obtained from TimeSeriesModel[…]["property"].
- The value of the model at time t can be obtained by giving model[t]. If t is in the range of the input data, then the data at time t is returned; otherwise, a forecasted value is given.
- Forecast prediction limits at a time t can be obtained using model["PredictionLimits"][t].
- Normal gives the underlying time series process for the time series model.
- TimeSeriesModel[…][prop,ann] gives the annotation ann associated with the property prop.
- Possible time series model properties are listed on the page for TimeSeriesModelFit.
Examples
open allclose allBasic Examples (1)
Create a TimeSeriesModel from some data:
Extract a property from the model:
Evaluate the time series model at time 100:
Use Normal to obtain the underlying time series process:
Scope (7)
Extract a property from a TimeSeriesModel:
Evaluate the time series model at a point:
Evaluate the time series model at a date:
Obtain the underlying time series process:
Use the original data to simulate future observations with TimeSeriesModel:
Fit a model using TimeSeriesModelFit:
Use the best fit process to simulate 10 future observations:
No information about time stamps or initial values is passed to RandomFunction:
Simulate using TimeSeriesModel to use information given by the original data:
Text
Wolfram Research (2014), TimeSeriesModel, Wolfram Language function, https://reference.wolfram.com/language/ref/TimeSeriesModel.html.
CMS
Wolfram Language. 2014. "TimeSeriesModel." Wolfram Language & System Documentation Center. Wolfram Research. https://reference.wolfram.com/language/ref/TimeSeriesModel.html.
APA
Wolfram Language. (2014). TimeSeriesModel. Wolfram Language & System Documentation Center. Retrieved from https://reference.wolfram.com/language/ref/TimeSeriesModel.html