Advanced Statistical Methods in Data Science

Description: Advanced Statistical Methods in Data Science Please note: this item is printed on demand and will take extra time before it can be dispatched to you (up to 20 working days). Author(s): Ding-Geng Chen, Jiahua Chen, Xuewen Lu, Grace Y. Yi, Hao Yu Format: Hardback Publisher: Springer Verlag, Singapore, Singapore Imprint: Springer Verlag, Singapore ISBN-13: 9789811025938, 978-9811025938 Synopsis This book gathers invited presentations from the 2nd Symposium of the ICSA- CANADA Chapter held at the University of Calgary from August 4-6, 2015. The aim of this Symposium was to promote advanced statistical methods in big-data sciences and to allow researchers to exchange ideas on statistics and data science and to embraces the challenges and opportunities of statistics and data science in the modern world. It addresses diverse themes in advanced statistical analysis in big-data sciences, including methods for administrative data analysis, survival data analysis, missing data analysis, high-dimensional and genetic data analysis, longitudinal and functional data analysis, the design and analysis of studies with response-dependent and multi-phase designs, time series and robust statistics, statistical inference based on likelihood, empirical likelihood and estimating functions. The editorial group selected 14 high-quality presentations from this successful symposium and invited the presenters to prepare a full chapter for this book in order to disseminate the findings and promote further research collaborations in this area. This timely book offers new methods that impact advanced statistical model development in big-data sciences.

Price: 79.47 GBP

Location: Aldershot

End Time: 2024-12-26T17:13:11.000Z

Shipping Cost: 30.05 GBP