Modality, runs, strings and wavelets
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Summary
It is shown that the number and location of local extreme values are consistently estimated and the rate of convergence of the taut string-wavelet method is almost optimal and the method is extremely sensitive being able to detect very low power peaks.
- Type
- preprint
- Published
- 1999-01-01
- Cited by
- 0
- References
- 30
- Access
- Open access
- OpenAlex
- https://openalex.org/W19049093
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:14518107
Keywords
Wavelet, Maxima and minima, Section (typography), Outlier, String (physics)
References
- Wavelet Shrinkage: Asymptopia?
- Some Aspects of the Spline Smoothing Approach to Non‐Parametric Regression Curve Fitting
- Local polynomial modelling and its applications
- On Estimating Regression
- Estimating smooth monotone functions
- The Dip Test of Unimodality
- Nonparametric regression under qualitative smoothness assumptions
- A Lower Bound on the Risks of Non-Parametric Estimates of Densities in the Uniform Metric
- Smoothing Splines and Shape Restrictions
- The Mode Tree: A Tool for Visualization of Nonparametric Density Features
- Asymptotic Distributions of Slope-of-Greatest-Convex-Minorant Estimators
- Variational solution of penalized likelihood problems and smooth curve estimation
- Locally adaptive regression splines
- Statistical Inference Under Order Restrictions
- Nonparametric testing of the existence of modes
- Estimating a Regression Function
- Density Estimation and Bump-Hunting by the Penalized Likelihood Method Exemplified by Scattering and Meteorite Data
- Smooth regression analysis
- Extending the Scope of Wavelet Regression Methods by Coefficient-Dependent Thresholding
- An Introduction to Probability Theory and its Applications, Volume I
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