Maximum Penalized Likelihood Estimation: Volume II: Regression: 2 (Springer Series in Statistics)

by Paul P. Eggermont (Author), Vincent N. LaRiccia (Author)

• New

  Hardcover
  2009

  $226.53

  Unique blend of asymptotic theory and small sample practice through simulation experiments and data analysis. Novel reproducing kernel Hilbert space methods for the analysis of smoothing splines and local polynomials. Leading to uniform error bounds and honest confidence bands for the mean function using smoothing splines Exhaustive exposition of algorithms, including the Kalman filter, for the computation of smoothing splines of arbitrary order.