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# Thread Subject: Variation of ARX model

 Subject: Variation of ARX model From: Guanqun Date: 25 Feb, 2009 01:31:02 Message: 1 of 2 Hi~! I need to solve a variation of ARX model: y(t)=C+\sigma a_k*x(t-k)+\sigma b_k*y(t-k)+e(t), where C is a constant. I looked up in the SYSTEM ID toolbox but didn't find useful function. I wonder if any functions any realize that. Thanks
 Subject: Variation of ARX model From: Rajiv Singh Date: 25 Feb, 2009 14:55:43 Message: 2 of 2 You mean you need a model with affine term? Note that the model with non zero C is not a linear model. However, you should be able to use a nonlinear ARX (idnlarx) model to estimate this; see help for estiamtor NLARX and model IDNLARX. Model = nlarx(data, [na nb nk], []) This model has no nonlinearity (nonlinearity = 'linear'), so it basically estimates something very similar to a linear ARX model, except that it also captures the offset (C). The values of the ARX coefficients and the offset are stored in Model.Nonlinearity.Parameters in fields LinearCoeff and OutputOffset. If C is known in advance, it would be better to remove it from y and then use the detrended data with ARX to estimate a linear model. -rajiv "Guanqun " wrote in message news:go270m$kvc$1@fred.mathworks.com... > Hi~! I need to solve a variation of ARX model: > y(t)=C+\sigma a_k*x(t-k)+\sigma b_k*y(t-k)+e(t), where C is a constant. > > I looked up in the SYSTEM ID toolbox but didn't find useful function. I > wonder if any functions any realize that. Thanks