Abstract
The choice of the smoothing parameter in nonparametric regression is critical to the form
of the estimated curve and any inference that follows. Many methods are available that
will generate a single choice for this parameter. Here we argue that the considerable uncertainty
in this choice should be explicitly represented.
The construction of standard simultaneous confidence bands in nonparametric regression often requires difficult
mathematical arguments. We question their practical utility, presenting several deficiencies.
We propose a new kind of confidence band that reflects the uncertainty regarding the smoothness
of the estimate.
Original language | English |
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Pages (from-to) | 4-10 |
Journal | Stat |
Volume | 5 |
Issue number | 1 |
Early online date | 10 Jan 2016 |
DOIs | |
Publication status | Published - 2016 |
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Dive into the research topics of 'Confidence bands for smoothness in nonparametric regression'. Together they form a unique fingerprint.Profiles
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Julian Faraway
- Department of Mathematical Sciences - Professor
- EPSRC Centre for Doctoral Training in Statistical Applied Mathematics (SAMBa)
Person: Research & Teaching