Package Scientific :: Package Signals :: Module Models :: Class AveragedAutoRegressiveModel

Class AveragedAutoRegressiveModel

AutoRegressiveModel --+
                      |
                     AveragedAutoRegressiveModel

Averaged auto-regressive model for stochastic process

An averaged model is constructed by averaging the model coefficients of several auto-regressive models of the same order. An averaged model is created empty, then individual models are added.

Instance Methods

[hide private]

__init__(self, order, delta_t)

add(self, model, weight=1)
Adds the coefficients of an autoregressive model to the average.

Inherited from AutoRegressiveModel: correlation, frictionConstant, memoryFunction, memoryFunctionZ, memoryFunctionZapprox, poles, predictStep, spectrum

Inherited from AutoRegressiveModel (private): _findCoefficients, _setTrajectory

Method Details

[hide private]

init(self, order, delta_t)
(Constructor)

Parameters:

order (int) - the order of the model
delta_t (float) - the sampling interval for the time series

Overrides: AutoRegressiveModel.__init__

add(self, model, weight=1)

Adds the coefficients of an autoregressive model to the average.

Parameters:

model (AutoRegressiveModel) - an autoregressive model
weight (float) - the weight of the model in the average

Raises:

ValueError - if the order of the model does not match the order of the average model

Class AveragedAutoRegressiveModel

__init__(self, order, delta_t) (Constructor)

add(self, model, weight=1)

init(self, order, delta_t)
(Constructor)