Advanced Statistical Methods in Data Science - download pdf or read online

By Ding-Geng Chen, Jiahua Chen, Xuewen Lu, Grace Y. Yi, Hao Yu

ISBN-10: 9811025932

ISBN-13: 9789811025938

ISBN-10: 9811025940

ISBN-13: 9789811025945

This booklet gathers invited shows from the 2d Symposium of the ICSA- CANADA bankruptcy held on the college of Calgary from August 4-6, 2015. the purpose of this Symposium used to be to advertise complicated statistical equipment in big-data sciences and to permit researchers to interchange rules on facts and knowledge technological know-how and to embraces the demanding situations and possibilities of data and information technological know-how within the glossy international. It addresses assorted topics in complex statistical research in big-data sciences, together with equipment for administrative information research, survival facts research, lacking info research, high-dimensional and genetic info research, longitudinal and practical facts research, the layout and research of reviews with response-dependent and multi-phase designs, time sequence and strong facts, statistical inference according to probability, empirical chance and estimating services. The editorial workforce chosen 14 high quality displays from this profitable symposium and invited the presenters to arrange a whole bankruptcy for this publication in an effort to disseminate the findings and advertise extra examine collaborations during this quarter. This well timed publication bargains new equipment that impression complex statistical version improvement in big-data sciences.

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1 presents the histogram of the LOS for IHD patients from Saskatchewan in 2011. 24 %/ had same-day surgery, which constitutes the zero counts in LOS. Among those inpatients who stayed in hospital overnight, the number of days ranged from 1 to 156, with 75 % having fewer than a week of stay. Suppose that the data were generated under an independent and identically distributed Poisson regression with mean parameter as the mean 4:5 days, which is the mean of the LOS in our data. Under such model, we would expect about 1 % of zeros, which is far fewer 0s than observed.

This is followed by the application of the model to the data, and then results are presented. Discussion on the results and limitations of the study conclude this Chapter. 1 Data We used hospital discharge administrative database with the admission date ranging between January 1 and December 31 in 2011 due to IHD, which was provided by the Saskatchewan Ministry of Health. These administrative databases produced by every acute care hospital in the province of Saskatchewan, provide the following information from every single admission: age, gender, admission and discharge dates, the patient’s areas of residence, and diagnosis and procedure codes [International Classification of disease (ICD) 10th revision Clinical Modification Code – I20 – I25 for IHD].

We first describe the data. Next, we specify the models and outline the Bayesian approach used for model estimation. This is followed by the application of the model to the data, and then results are presented. Discussion on the results and limitations of the study conclude this Chapter. 1 Data We used hospital discharge administrative database with the admission date ranging between January 1 and December 31 in 2011 due to IHD, which was provided by the Saskatchewan Ministry of Health. These administrative databases produced by every acute care hospital in the province of Saskatchewan, provide the following information from every single admission: age, gender, admission and discharge dates, the patient’s areas of residence, and diagnosis and procedure codes [International Classification of disease (ICD) 10th revision Clinical Modification Code – I20 – I25 for IHD].

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Advanced Statistical Methods in Data Science by Ding-Geng Chen, Jiahua Chen, Xuewen Lu, Grace Y. Yi, Hao Yu


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