Nonparametric function estimation with stochastic data, otherwise known as smoothing, has been studied by several generations of statisticians. Assisted by the ample computing power in today's servers, desktops, and laptops, smoothing methods have been finding their ways into everyday data analysis
โฆ LIBER โฆ
Local and global asymptotic inference in smoothing spline models
โ Scribed by Shang, Zuofeng; Cheng, Guang
- Book ID
- 125856468
- Publisher
- Institute of Mathematical Statistics
- Year
- 2013
- Tongue
- English
- Weight
- 384 KB
- Volume
- 41
- Category
- Article
- ISSN
- 0090-5364
No coin nor oath required. For personal study only.
๐ SIMILAR VOLUMES
[Springer Series in Statistics] Smoothin
โ
Gu, Chong
๐
Article
๐
2012
๐
Springer New York
๐
English
โ 364 KB
Statistical inference in the partial lin
โ
He, Hua; Tang, Wan; Zuo, Guoxin
๐
Article
๐
2014
๐
Elsevier Science
๐
English
โ 441 KB
Fast and Accurate Inference for the Smoo
โ
Paige, Robert L.; Trindade, A. Alexandre
๐
Article
๐
2013
๐
John Wiley and Sons
๐
English
โ 281 KB
Choice of scale for cubic smoothing spli
โ
Patrick Royston
๐
Article
๐
2000
๐
John Wiley and Sons
๐
English
โ 192 KB
The determination of the functional form of the relationship between an outcome variable and one or more continuous covariates is an important aspect of the modelling of medical data. For correct interpretation of the data it is essential that the functional form be speci"ed at least approximately c
Odds ratio estimation in Bernoulli smoot
โ
Yuedong Wang
๐
Article
๐
1997
๐
John Wiley and Sons
โ 333 KB
[Lecture Notes in Statistics] Asymptotic
โ
Basawa, Ishwar V.; Scott, David John
๐
Article
๐
1983
๐
Springer New York
โ 611 KB