List of Matlab codes for Model Order Reduction and a demonstration example: cluster_data.m data clustering and centroids generation modeln.m code for the simulation of the linearized full order model modelq.m code for the simulation of the reduced order model BArnoldi_wDF.m Block Arnoldi algorithm with deflation Freund's version for MIMO system projection basis generation arnoldi.m Arnoldi algorithm for SISO system projection basis generation trajectory_merge.m merging a set of trajectories exp_pts.m generation of linearization points of a single trajectory as described in TPWL method Increase_k.m increasing the number of clusters in a behavioral region during the MOR refinement process Increase_kR.m increasing the number of clusters and the number of behavioral regions during the MOR refinement process Increase_R.m increasing the number of behavioral regions during the MOR refinement process paramdist.m generation of Gaussian or Uniform distribution for statistical simulation paramgen.m generation of Gaussian or uniform samples of the parameters vth, kp, and kn variations for statistical simulation The above codes can be used for the MOR of a given model but it requires 2 matlab functions: the original full order ode model and its Jacobian. Ring_osc_model.zip a MOR demonstration example