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 even if the noise is IND. A new cost function is obtained via the maximum likelihood principle; superior results are illustrated both for small data sets and infinitely long data streams.Comment: RevTex, 11 pages, 4 figure

Retroperitoneal Colon Perforation with Review of Retroperitoneal Anatomic Relationships: Case Series with Review of Literature

We present two cases of iatrogenic retroperitoneal perforation involving the ascending and descending colon. The unique imaging findings in these two cases demonstrate potential routes of communication for air originating in the retroperitoneum. In context of these cases, we review the clinical presentation, management, and anatomic features of retroperitoneal perforation. Along with clinical history, an understanding of retroperitoneal anatomic relationships can aid radiologists in identifying the origin of perforation