Unimodal regression using Bernstein–Schoenberg splines and penalties
From MaRDI portal
Publication:3465354
DOI10.1111/biom.12193zbMath1393.62075OpenAlexW1891457878WikidataQ45676127 ScholiaQ45676127MaRDI QIDQ3465354
Claudia Köllmann, Katja Ickstadt, Björn Bornkamp
Publication date: 21 January 2016
Published in: Biometrics (Search for Journal in Brave)
Full work available at URL: http://hdl.handle.net/2003/37180
Nonparametric regression and quantile regression (62G08) Numerical computation using splines (65D07) Applications of statistics to biology and medical sciences; meta analysis (62P10)
Related Items
Change-point estimation using shape-restricted regression splines ⋮ On estimation of isotonic piecewise constant signals ⋮ Adaptive risk bounds in unimodal regression ⋮ Optimal rates of statistical seriation
Uses Software
Cites Work
- Unnamed Item
- Semiparametric regression with shape-constrained penalized splines
- Totally positive bases for shape preserving curve design and optimality of \(B\)-splines
- Slice sampling. (With discussions and rejoinder)
- Flexible smoothing with \(B\)-splines and penalties. With comments and a rejoinder by the authors
- Shape restricted nonparametric regression with Bernstein polynomials
- Efficient algorithms for generating truncated multivariate normal distributions
- On robust cross-validation for nonparametric smoothing
- An identity for spline functions with applications to variation diminishing spline approximation
- Dose-Response Curve Estimation: A Semiparametric Mixture Approach
- Constrained penalized splines
- Asymptotic properties of penalized spline estimators
- Monotonic Smoothing Splines Fitted by Cross Validation
- Model Selection: An Integral Part of Inference
- Bayesian Survival Analysis Using Bernstein Polynomials
- A transformation approach for incorporating monotone or unimodal constraints
- Combining Multiple Comparisons and Modeling Techniques in Dose‐Response Studies