Ahmed, S. Ejaz
Big and Complex Data Analysis
Part I. General High-Dimensional Theory and Methods
1. Regularization After Marginal Learning for Ultra-High Dimensional Regression Models
Yang Feng, Mengjia Yu
2. Empirical Likelihood Test for High Dimensional Generalized Linear Models
Yangguang Zang, Qingzhao Zhang, Sanguo Zhang, Qizhai Li, Shuangge Ma
3. Random Projections for Large-Scale Regression
Gian-Andrea Thanei, Christina Heinze, Nicolai Meinshausen
4. Testing in the Presence of Nuisance Parameters: Some Comments on Tests Post-Model-Selection and Random Critical Values
Hannes Leeb, Benedikt M. Pötscher
5. Analysis of Correlated Data with Error-Prone Response Under Generalized Linear Mixed Models
Grace Y. Yi, Zhijian Chen, Changbao Wu
6. Bias-Reduced Moment Estimators of Population Spectral Distribution and Their Applications
Yingli Qin, Weiming Li
Part II. Network Analysis and Big Data
7. Statistical Process Control Charts as a Tool for Analyzing Big Data
Peihua Qiu
8. Fast Community Detection in Complex Networks with a
Yahui Tian, Yulia R. Gel
9. How Different Are Estimated Genetic Networks of Cancer Subtypes?
Ali Shojaie, Nafiseh Sedaghat
10. A Computationally Efficient Approach for Modeling Complex and Big Survival Data
Kevin He, Yanming Li, Qingyi Wei, Yi Li
11. Tests of Concentration for Low-Dimensional and High-Dimensional Directional Data
Christine Cutting, Davy Paindaveine, Thomas Verdebout
12. Nonparametric Testing for Heterogeneous Correlation
Stephen Bamattre, Rex Hu, Joseph S. Verducci
Part III. Statistics Learning and Applications
13. Optimal Shrinkage Estimation in Heteroscedastic Hierarchical Linear Models
S. C. Kou, Justin J. Yang
14. High Dimensional Data Analysis: Integrating Submodels
Syed Ejaz Ahmed, Bahadır Yüzbaşı
15. High-Dimensional Classification for Brain Decoding
Nicole Croteau, Farouk S. Nathoo, Jiguo Cao, Ryan Budney
16. Unsupervised Bump Hunting Using Principal Components
Daniel A. Díaz-Pachón, Jean-Eudes Dazard, J. Sunil Rao
17. Identifying Gene–Environment Interactions Associated with Prognosis Using Penalized Quantile Regression
Guohua Wang, Yinjun Zhao, Qingzhao Zhang, Yangguang Zang, Sanguo Zang, Shuangge Ma
18. A Mixture of Variance-Gamma Factor Analyzers
Sharon M. McNicholas, Paul D. McNicholas, Ryan P. Browne
Avainsanat: Statistics, Statistical Theory and Methods, Statistics and Computing/Statistics Programs, Big Data/Analytics, Biostatistics, Data Mining and Knowledge Discovery
- Toimittaja
- Ahmed, S. Ejaz
- Julkaisija
- Springer
- Julkaisuvuosi
- 2017
- Kieli
- en
- Painos
- 1
- Sarja
- Contributions to Statistics
- Sivumäärä
- 14 sivua
- Kategoria
- Eksaktit luonnontieteet
- Tiedostomuoto
- E-kirja
- eISBN (PDF)
- 9783319415734
- Painetun ISBN
- 978-3-319-41572-7