General Asymptotic Confidence Bands Based on Kernel-type Function Estimators
By Paul Deheuvels, David Mason. 2004
87 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/50717827adb94f62c4ffe05aad6bfc85f89ff909
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Rafael Weißbach
- Dominik Wied
- U. Einmahl
- David Mason
- Yen-Chi Chen
- Richard Nickl
- Arun K. Kuchibhotla
- Abhishek Chakrabortty
In Statistics and Probability
- David Mason
- U. Einmahl
- Dominik Wied
- Rafael Weißbach
- Evarist Gin'e
- Richard Nickl
- Yen-Chi Chen
- Vladimir Koltchinskii
Citations in the corpus
- On local U-statistic processes and the estimation of densities of functions of several sample variables (2007, unknown): “11) refer to Deheuvels and Mason [5].”
- Uniform in bandwidth consistency of kernel-type function estimators (2005, methodology): “MR1783500 [6] Deheuvels, P. and Mason, D. M. (1992).”
- Consistency of the kernel density estimator: a survey (2012, methodology): “Some techniques have even been developed to account for such bandwidth sequences, such as those with plug-in-estimators from Deheuvels and Mason (2004), or for the nearest-neighbor bandwidth from Schäfer (1986) and Weißbach (2006).”
- Simultaneous confidence bands for nonparametric regression with functional data (2009, unknown): “We also point to Baraud (2004) for the computation of SCI on an increasing number of (fixed) design points, and to Deheuvels and Mason (2004) for SCB with asymptotic coverage level 100%.”