filters data using the time series model given by tproc.
- KalmanFilter allows data to be a list or TemporalData.
- All the parameters in the time series model tproc must be numeric.
- KalmanFilter output is decided by the type of the input. The first element of the output is initialized to be zero, so the length of the output agrees with the length of the input.
Examplesopen allclose all
Basic Examples (2)
Consider the following time series data and determine whether it is adequately modeled by a MAProcess:
The correlation function drops off after lag 3. This is evidence of an MAProcess:
Fit an MAProcess model to the data:
Analyze residuals in TimeSeriesModel:
Compare to residuals from TimeSeriesModelFit:
Properties & Relations (1)
Possible Issues (1)
KalmanFilter requires the process to have all parameters numeric: