Nonparametric regression using locally weighted least squares was first discussed by Stone and by Cleveland. Recently, it was shown by Fan and by Fan and Gijbels that the local linear kernel-weighted ...

Fan, Heckman and Wand proposed locally weighted kernel polynomial regression methods for generalized linear models and quasilikelihood functions. When the covariate variables are missing at random, we ...

Simply collecting data is not enough. You can fill spreadsheets with data, but it's useless if you can't act on it. Regression is one of the most powerful statistical tools for finding relationships ...