Principles and Methods for Data Science: Volume 43 (Hardcover)

1. Competing risks, aims and methods Ronald Geskus 2. Data analysis and mining of microbial community dynamics Shinji Nakaoka 3. Support Vector Machines, a robust prediction method with applications in bioinformatics Arnout Van Messem 4. Data Science - Concepts, Algorithms and Practice Kalidas Yeturu 5. Bayesian Model Selection for Data with High Dimensions Naveen Naidu Narisetty 6. High dimensional statistical inference: theoretical development to data analytics Deepak Ayyala 7. Big data challenges in genomics Hongyan Xu 8. Analysis of microarray gene expression data using information theory and stochastic algorithm Narayan Behera 9. Hybrid Models Arni S.R. Srinivasa Rao 10. Markov Chain Monte Carlo Methods: Theory and Practice David Spade