Nonparametric Regression Estimation in the Heteroscedastic Errors-in-Variables Problem

By Aurore Delaigle, A. Meister. 2007

74 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Control and Systems Engineering, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/6d55712506ee683619bd7b1955370ddd87decdc5

How researchers see this paper

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

In Computer Networks and Communications

1. David Ruppert
2. John W. Staudenmayer
3. John P. Buonaccorsi

In Control and Systems Engineering

1. David Ruppert
2. John W. Staudenmayer
3. John P. Buonaccorsi

In Statistics and Probability

1. John P. Buonaccorsi
2. John W. Staudenmayer
3. David Ruppert
4. Robert Tibshirani
5. Paulo Cortez
6. Trevor J. Hastie
7. Jane Elith
8. Blaine Nelson

Citations in the corpus

• Density Estimation in the Presence of Heteroscedastic Measurement Error (2008, methodology): “Whereas the quite innovative method of Delaigle and Meister (2007a) can estimate the measurement error distribution nonparametrically, we used a version of their code (which they generously provided) that correctly assumes normal measurement error.”