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In this paper we propose a simulation-based analog circuit sizing method which is capable of significantly reducing the computational cost via adaptive response surface modeling. The proposed algorithm is based on the selective evaluation of a response surface model coupled with numerical circuit simulation and the adaptive update of the model for accuracy. An effective sampling scheme for modeling using two related criteria that are crucial for speedup and convergence towards an optimal solution is presented. One provides sufficient samples for model accuracy and convergence, whereas the other prevents oversampling of the design space after the model is saturated. Multivariate adaptive regression splines (MARS) are used to construct a model of the selected cost function. Results for several test functions and two test cases are discussed.