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Perspectives on Big Data Analysis: Methodologies and Applications
About this Title
S. Ejaz Ahmed, Brock University, St. Catharines, Ontario, Canada, Editor
Publication: Contemporary Mathematics
Publication Year:
2014; Volume 622
ISBNs: 978-1-4704-1042-1 (print); 978-1-4704-1887-8 (online)
DOI: https://doi.org/10.1090/conm/622
ReadershipTable of Contents
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Front/Back Matter
Articles
- Fan Yang, Kjell Doksum and Kam-Wah Tsui – Principal Component Analysis (PCA) for high-dimensional data. PCA is dead. Long live PCA
- Nozer D. Singpurwalla and Joshua Landon – Solving a System of High-Dimensional Equations by MCMC
- Jian Kang and Timothy D. Johnson – A slice sampler for the hierarchical Poisson/Gamma random field model
- Annaliza McGillivray and Abbas Khalili – A new penalized quasi-likelihood approach for estimating the number of states in a hidden Markov model
- Xiaoli Gao and S. Ejaz Ahmed – Efficient adaptive estimation strategies in high-dimensional partially linear regression models
- Hemant Ishwaran and J. Sunil Rao – Geometry and properties of generalized ridge regression in high dimensions
- Guoqing Diao, Bret Hanlon and Anand N. Vidyashankar – Multiple testing for high-dimensional data
- Frank Konietschke, Yulia R. Gel and Edgar Brunner – On multiple contrast tests and simultaneous confidence intervals in high-dimensional repeated measures designs
- Zhouwang Yang, Huizhi Xie and Xiaoming Huo – Data-driven smoothing can preserve good asymptotic properties
- Pang Du, Pan Wu and Hua Liang – Variable selection for ultra-high-dimensional logistic models
- Shakhawat Hossain and S. Ejaz Ahmed – Shrinkage estimation and selection for a logistic regression model
- Pooyan Khajehpour Tadavani, Babak Alipanahi and Ali Ghodsi – Manifold unfolding by Isometric Patch Alignment with an application in protein structure determination