Confidence sets for the maximizers of intensity functions
From MaRDI portal
Publication:2386159
DOI10.1016/j.jspi.2004.04.008zbMath1066.62050OpenAlexW1991109163WikidataQ61826151 ScholiaQ61826151MaRDI QIDQ2386159
Wen-Tao Huang, Andreas Futschik
Publication date: 22 August 2005
Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.jspi.2004.04.008
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Asymptotic optimality of the least-squares cross-validation bandwidth for kernel estimates of intensity functions
- The dip test of unimodality
- Simulated power functions
- On weak convergence and optimality of kernel density estimates of the mode
- On confidence bands in nonparametric density estimation and regression
- Some asymptotics for multimodality tests based on kernel density estimates
- Weak and strong uniform consistency of the kernel estimate of a density and its derivatives
- On mode testing and empirical approximations to distributions
- Subsampling
- On the minimisation of \(L^ p\) error in mode estimation
- On some global measures of the deviations of density function estimates
- Estimation of the mode
- A Kernel Method for Smoothing Point Process Data
- Equivalence of Smoothing Parameter Selectors in Density and Intensity Estimation
- An approximation of partial sums of independent RV'-s, and the sample DF. I
- Bootstrap Confidence Regions for the Intensity of a Poisson Point Process
- On Estimation of a Probability Density Function and Mode
- On bootstrapping the mode in the nonparametric regression model with random design