KalmanFilter

KalmanFilter[tproc, data]
filters data using the time series model given by tproc.

DetailsDetails

  • KalmanFilter allows data to be a vector 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.

ExamplesExamplesopen allclose all

Basic Examples (3)Basic Examples (3)

Find a one-step-ahead prediction using an autoregressive model:

In[1]:=
Click for copyable input
Out[1]=

Find a one-step-ahead prediction using a moving-average model:

In[1]:=
Click for copyable input
In[2]:=
Click for copyable input
Out[2]=

Show path:

In[3]:=
Click for copyable input
Out[3]=

Filter noise from a sample path using an ARMA model:

In[1]:=
Click for copyable input
In[2]:=
Click for copyable input
Out[2]=

Find filtered data:

In[3]:=
Click for copyable input
Out[3]=
In[4]:=
Click for copyable input
Out[4]=

Compare the data to the prediction:

In[5]:=
Click for copyable input
Out[5]=
New in 9
New to Mathematica? Find your learning path »
Have a question? Ask support »