Generalized fiducial inference for wavelet regression
By Jan Hannig, Thomas C.M. Lee. 2009
63 citations recorded by the source corpus.
Subfields: Computer Vision and Pattern Recognition, Statistics and Probability, Signal Processing
View Paper: https://www.semanticscholar.org/paper/45cb9ffd4547637d8c74fd9ebbd8e6afac050a68
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computer Vision and Pattern Recognition
In Statistics and Probability
- Ryan Martin
- Jan Hannig
- Randy C. S. Lai
- Hari Iyer
- Thomas C.M. Lee
- Chuanhai Liu
- Peng Ding
- Andrew Gelman
In Signal Processing
Citations in the corpus
- A note on p-values interpreted as plausibilities (2012, background): “The IM framework has some connections with existing approaches, such as fiducial (Hannig 2009, 2013; Hannig and Lee 2009), confidence distributions (Xie and Singh 2013; Xie et al. 2011), Dempster–Shafer theory (Dempster 2008; Shafer 1976, 2011), generalized p-values and confidence intervals (Chiang…”
- Generalized Fiducial Inference: A Review and New Results (2016, methodology): “Hannig and Lee (2009) used GFI to perform the second step.”
- Generalized fiducial inference via discretization (2013, background): “More complicated computational schemes for generalized fiducial inference can be also found in Hannig and Lee (2009), Wandler and Hannig (2011) and elsewhere.”