Interface for smoothing functions
bkfsmooth(y, x, df, smoother = "spline", w = rep(1, length(y)))
smoothed values
diagonal of the influence matrix
degrees of freedom
dependent variable for fitting. In semiparametric models, this is the partial residuals of parametric fit
independent variable. Univariate fit only
equivalent degrees of freedom. If NULL the smoothing parameter is selected by cross-validation
string with the name of the smoother to be used
vector with the diagonal elements of the weight matrix. Default is a vector of \(1\) with the same length of \(y\)
Washington Leite Junger wjunger@ims.uerj.br and Antonio Ponce de Leon ponce@ims.uerj.br
Although several smoothers can be used in semiparametric regression models, only natural cubic splines is intended to be used in Poisson-Gamma Additive Models due to its interesting mathematical properties.
Nowadays, this function interfaces the smooth.spline in stats library. It will become not dependent soon enough.
Green, P. J., Silverman, B. W. (1994) Nonparametric Regression and Generalized Linear Models: a roughness penalty approach. Chapman and Hall, London
Hastie, T. J., Tibshirani, R. J.(1990) Generalized Additive Models. Chapman and Hall, London
Junger, W. L. (2004) Semiparametric Poisson-Gamma models: a roughness penalty approach. MSc Dissertation. Rio de Janeiro, PUC-Rio, Department of Electrical Engineering.
pgam, predict.pgam