## Discussion 'Model selection for generalized linear models with factor-augmented predictors' Professors Ando and Tsay should be congratulated for such nice work, which provides an effective statistical method to handle high-dimensional data sets with generalized linear models. In this discussio
Quantile regression models with factor-augmented predictors and information criterion
β Scribed by Tomohiro Ando; Ruey S. Tsay
- Book ID
- 110880148
- Publisher
- John Wiley and Sons
- Year
- 2011
- Tongue
- English
- Weight
- 292 KB
- Volume
- 14
- Category
- Article
- ISSN
- 1368-4221
No coin nor oath required. For personal study only.
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We would like to thank all the discussants for their wide-ranging discussions and constructive suggestions. They provide many useful references and directions for further research. We organize our reply in sections and hope that they can attract more discussions and encourage deeper research and dev
## Abstract This paper considers generalized linear models in a dataβrich environment in which a large number of potentially useful explanatory variables are available. In particular, it deals with the case that the sample size and the number of explanatory variables are of similar sizes. We adopt
We congratulate the authors for contributing such an innovative paper in terms of both modeling methodology and subject matter significance. This paper enriches the application of generalized linear models in a data-rich environment. The principal component method was first applied to reduce the num