The Role of Pseudo Data for Robust Smoothing with Application to Wavelet Regression

By Hee‐Seok Oh, D. Nychka, Thomas C.M. Lee. 2007

54 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/0b6bbeb0731cac1783db6bdff34eec683851bf19

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Vision and Pattern Recognition

1. Monica Pratesi
2. Maria Giovanna Ranalli
3. Nicola Salvati

In Statistics and Probability

1. Monica Pratesi
2. Maria Giovanna Ranalli
3. Nicola Salvati

Citations in the corpus

• Nonparametric M-quantile regression using penalised splines (2009, methodology): “[31] on robust p-splines proposes an algorithm based on iterative least squares with a pseudo-response variable that uses Winsorised residuals.”