Semiparametric Regression Model With Natural Spline and Systematic Error Estimation

The semiparametric regression is discussed by natural spline fitting. According to penalized least squares, Cubic natural spline forms penalized item. The choice of smoothing parameter can be automatically obtained by using generalized cross-validation function. Estimators of penalized least square for parametric regression and vectors and spline function can be got by compiled program.