This book PDF is perfect for those who love Business & Economics genre, written by Inge Koch and published by Cambridge University Press which was released on 26 April 2024 with total hardcover pages 531. You could read this book directly on your devices with pdf, epub and kindle format, check detail and related Analysis of Multivariate and High Dimensional Data books below.
| Author | : Inge Koch |
| File Size | : 54,5 Mb |
| Publisher | : Cambridge University Press |
| Language | : English |
| Release Date | : 26 April 2024 |
| ISBN | : 9780521887939 |
| Pages | : 531 pages |
This modern approach integrates classical and contemporary methods, fusing theory and practice and bridging the gap to statistical learning.
This modern approach integrates classical and contemporary methods, fusing theory and practice and bridging the gap to statistical learning.
Get BookMultivariate analysis is a mainstay of statistical tools in the analysis of biomedical data. It concerns with associating data matrices of n rows by p columns, with rows representing samples (or patients) and columns attributes of samples, to some response variables, e.g., patients outcome. Classically, the sample size n
Get BookA comprehensive examination of high-dimensional analysis of multivariate methods and their real-world applications Multivariate Statistics: High-Dimensional and Large-Sample Approximations is the first book of its kind to explore how classical multivariate methods can be revised and used in place of conventional statistical tools. Written by prominent researchers in the field,
Get BookHigh-dimensional data appear in many fields, and their analysis has become increasingly important in modern statistics. However, it has long been observed that several well-known methods in multivariate analysis become inefficient, or even misleading, when the data dimension p is larger than, say, several tens. A seminal example is the
Get BookThis book features research contributions from The Abel Symposium on Statistical Analysis for High Dimensional Data, held in Nyvågar, Lofoten, Norway, in May 2014. The focus of the symposium was on statistical and machine learning methodologies specifically developed for inference in “big data” situations, with particular reference to genomic applications.
Get BookMethods for estimating sparse and large covariance matrices Covariance and correlation matrices play fundamental roles in every aspect of the analysis of multivariate data collected from a variety of fields including business and economics, health care, engineering, and environmental and physical sciences. High-Dimensional Covariance Estimation provides accessible and comprehensive coverage
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Download or read online Large Sample Covariance Matrices and High dimensional Data Analysis written by Jianfeng Yao,Shurong Zheng,Zhidong Bai, published by Unknown which was released on 2015. Get Large Sample Covariance Matrices and High dimensional Data Analysis Books now! Available in PDF, ePub and Kindle.
Get BookEver-greater computing technologies have given rise to an exponentially growing volume of data. Today massive data sets (with potentially thousands of variables) play an important role in almost every branch of modern human activity, including networks, finance, and genetics. However, analyzing such data has presented a challenge for statisticians
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