Better Nonlinear Models from Noisy Data: Attractors with Maximum Likelihood
نویسندگان
چکیده
منابع مشابه
Better Nonlinear Models from Noisy Data: Attractors with Maximum Likelihood
A new approach to nonlinear modelling is presented which, by incorporating the global behaviour of the model, lifts shortcomings of both least squares and total least squares parameter estimates. Although ubiquitous in practice, a least squares approach is fundamentally flawed in that it assumes independent, normally distributed (IND) forecast errors: nonlinear models will not yield IND errors ...
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ژورنال
عنوان ژورنال: Physical Review Letters
سال: 1999
ISSN: 0031-9007,1079-7114
DOI: 10.1103/physrevlett.83.4285