Advanced Statistical Methods in Data Science is popular PDF and ePub book, written by Ding-Geng Chen in 2016-11-30, it is a fantastic choice for those who relish reading online the Mathematics genre. Let's immerse ourselves in this engaging Mathematics book by exploring the summary and details provided below. Remember, Advanced Statistical Methods in Data Science can be Read Online from any device for your convenience.
Advanced Statistical Methods in Data Science Book PDF Summary
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.
Detail Book of Advanced Statistical Methods in Data Science PDF
- Author : Ding-Geng Chen
- Release : 30 November 2016
- Publisher : Springer
- ISBN : 9789811025945
- Genre : Mathematics
- Total Page : 222 pages
- Language : English
- PDF File Size : 7,7 Mb
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