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# scipy.maxentropy.model.setsmooth

`model.``setsmooth`(sigma)

  Speficies that the entropy dual and gradient should be computed with a quadratic penalty term on magnitude of the parameters. This ‘smooths’ the model to account for noise in the target expectation values or to improve robustness when using simulation to fit models and when the sampling distribution has high variance. The smoothing mechanism is described in Chen and Rosenfeld, ‘A Gaussian prior for smoothing maximum entropy models’ (1999).

  The parameter ‘sigma’ will be squared and stored as self.sigma2.

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