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Robust regression and outlier detection Annick M. Leroy, Peter J. Rousseeuw
Publisher: Wiley

About robust regression, robust estimators and statistical procedures, outlier detection, extreme value theory, data cleaning, outlier detection in high dimensional data, non parametric statistics. Even if you exclude CCSM4 as an outlier the contribution to the trend since '96 from volcanic recovery in the model ensemble is about the same as the observed trend. Here is a plot of post 96 observations . Regression analysis identified outliers. The volcanic term is critical here – at the moment it looks to me as though the ENSO term is robust, and the solar fairly robust (and small) once a response function is included. Jeuken J, Sijben A, Alenda C, Rijntjes J, Dekkers M, Boots-Sprenger S, McLendon R, Wesseling P: Robust detection of EGFR copy number changes and EGFR variant III: Technical aspects and relevance for glioma diagnostics. Outlier identification was performed with regression analysis to detect data points at or beyond 95% confidence intervals for residuals. Robust Nonlinear Optimization MATLAB Code Download Please have a look in RANSAC_4_Nonlinear.m This code is not heavily tested. Robust Nonlinear Fitting by RANSAC (Outlier Tolerent Nonlinear Regression). Bjoerck A, Numerical methods for least squares problems. Rousseeuw PJ, Leroy AM, Robust regression and outlier detection.