Inheritance diagram for nipy.algorithms.statistics.models.nlsmodel:
Non-linear least squares model
Bases: nipy.algorithms.statistics.models.model.Model
Class representing a simple nonlinear least squares model.
Methods
SSE() | Sum of squares error. |
fit() | Fit a model to data. |
getZ() | Set Z into self |
getomega() | Set omega into self |
initialize() | Initialize (possibly re-initialize) a Model instance. |
next() | Do an iteration of fit |
predict([design]) | Get predicted values for design or self.design |
Initialize non-linear model instance
Parameters: | Y : ndarray
design : ndarray
f : callable
grad : callable
theta : array
niter : int
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Sum of squares error.
Returns: | sse: float :
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Fit a model to data.
Set Z into self
Returns: | None : |
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Set omega into self
Returns: | None : |
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Initialize (possibly re-initialize) a Model instance.
For instance, the design matrix of a linear model may change and some things must be recomputed.
Do an iteration of fit
Returns: | None : |
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Get predicted values for design or self.design
Parameters: | design : None or array, optional
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Returns: | y_predicted : array
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