NonlinearModelFit on correlated data
- To: mathgroup at smc.vnet.net
- Subject: [mg104861] NonlinearModelFit on correlated data
- From: L.J.A.Vasquez at warwick.ac.uk
- Date: Thu, 12 Nov 2009 06:02:04 -0500 (EST)
Hello. I want to perform a nonlinear model fitting on data points with some significant correlations in them. For these correlated data points, the definition of chi^2 is chi^2=Sum_i Sum_j [ y_i - f(y_i) ] * [ y_j - f(y_j) ] / Covariance(y_i, y_j) . Currently, I am using the Mathematica function "NonlinearModelFit" which unfortunately only assumes statistically independent data points and does not allow to incorporate correlation in the data points when estimating the best fit parameters. I have looked at other data fitting functions such as FindFit and even GeneralizedLinearFit but i haven't found one yet that takes into account correlated data. Maybe i am missing something. Is there a way to perform a nonlinear fit for a correlated data points? Is there a way to change how the chi^2 is being defined in any of the Mathematica fitting function? Perhaps, there is an additional Mathematica package that is available and deals with this problem. Any help is most welcome. With my best regards, -- Louella __________________________________ Louella Judy A. Vasquez Department of Physics and Centre for Scientific Computing University of Warwick, Coventry CV47AL United Kingdom PHONE: +44 (24) 765 74309 MOBILE: +44 790 4336687
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