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Titlebook: Mathematical and Statistical Applications in Life Sciences and Engineering; Avishek Adhikari,Mahima Ranjan Adhikari,Yogendra P Book 2017 S

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書(shū)目名稱Mathematical and Statistical Applications in Life Sciences and Engineering
編輯Avishek Adhikari,Mahima Ranjan Adhikari,Yogendra P
視頻videohttp://file.papertrans.cn/627/626707/626707.mp4
概述Collects articles on a wide spectrum of topics in mathematics and statistics and their applications.Presents a wide range of topics in communication theory, image processing, reliability and life-test
圖書(shū)封面Titlebook: Mathematical and Statistical Applications in Life Sciences and Engineering;  Avishek Adhikari,Mahima Ranjan Adhikari,Yogendra P Book 2017 S
描述.The book includes articles from eminent international scientists discussing a wide spectrum of topics of current importance in mathematics and statistics and their applications. It presents state-of-the-art material along with a clear and detailed review of the relevant topics and issues concerned. The topics discussed include message transmission, colouring problem, control of stochastic structures and information dynamics, image denoising, life testing and reliability, survival and frailty models, analysis of drought periods, prediction of genomic profiles, competing risks, environmental applications and chronic disease control. It is a valuable resource for researchers and practitioners in the relevant areas of mathematics and statistics..
出版日期Book 2017
關(guān)鍵詞Breast Cancer; Volatility Stochastic Models; Nonparametric Estimation; Bivariate Frailty Model; Bayesian
版次1
doihttps://doi.org/10.1007/978-981-10-5370-2
isbn_softcover978-981-13-3854-0
isbn_ebook978-981-10-5370-2
copyrightSpringer Nature Singapore Pte Ltd. 2017
The information of publication is updating

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Something Borrowed, Something New: Precise Prediction of Outcomes from Diverse Genomic Profilespredict colon cancer survival from DNA methylation profiles that vary by age groups, and identify those significant methylation sites that are shared across the age groups and those that are age-specific.
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On Bayesian Inference of , for Weibull Distributionthe covariates are also present. We further consider the case when the two shape parameters are different. Simulation experiments have been performed to see the effectiveness of the proposed methods. One data set has been analyzed for illustrative purposes and finally, we conclude the paper.
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