KalmanFilter.set_conserve_memory(conserve_memory=None, **kwargs)
[source]
Set the memory conservation method
By default, the Kalman filter computes a number of intermediate matrices at each iteration. The memory conservation options control which of those matrices are stored.
Parameters: |
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The memory conservation method is defined by a collection of boolean flags, and is internally stored as a bitmask. The methods available are:
predict
method from the results class is unavailable.Note that if using a Scipy version less than 0.16, the options MEMORY_NO_GAIN, MEMORY_NO_SMOOTHING, and MEMORY_NO_STD_FORECAST have no effect.
If the bitmask is set directly via the conserve_memory
argument, then the full method must be provided.
If keyword arguments are used to set individual boolean flags, then the lowercase of the method must be used as an argument name, and the value is the desired value of the boolean flag (True or False).
Note that the memory conservation method may also be specified by directly modifying the class attributes which are defined similarly to the keyword arguments.
The default memory conservation method is MEMORY_STORE_ALL
, so that all intermediate matrices are stored.
>>> mod = sm.tsa.statespace.SARIMAX(range(10)) >>> mod.ssm..conserve_memory 0 >>> mod.ssm.memory_no_predicted False >>> mod.ssm.memory_no_predicted = True >>> mod.ssm.conserve_memory 2 >>> mod.ssm.set_conserve_memory(memory_no_filtered=True, ... memory_no_forecast=True) >>> mod.ssm.conserve_memory 7
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© 2006–2008 Scipy Developers
© 2006 Jonathan E. Taylor
Licensed under the 3-clause BSD License.
http://www.statsmodels.org/stable/generated/statsmodels.tsa.statespace.kalman_filter.KalmanFilter.set_conserve_memory.html