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High-dimensional Data Analysis

Over the last few years, significant developments have been taking place in high-dimensional data analysis, driven primarily by a wide;

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Perspectives on Big Data Analysis

This volume contains the proceedings of the International Workshop on Perspectives on High-dimensional Data Analysis II, held May 30-June 1;

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Statistical Foundations of Data Science

Provides theoretical insights and justification of the statistical procedures for the analysis of high-dimensional data Presents a general;

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Exploration and Analysis of DNA Microarray and Other High-Dimensional Data

of Environmental Quality Exploration and Analysis of DNA Microarray and Other High-Dimensional Data, Second Edition provides comprehensive coverage;

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Multivariate Statistics

Written by well-known, award-winning authors, this is the first book to focus on high-dimensional data analysis while presenting real-world;

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Sparse representation of High Dimensional Data for Classification

In this book you will find the use of sparse Principal Component Analysis (PCA) for representing high dimensional data for classification;

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High-Dimensional Covariance Estimation

graduate-level courses in multivariate analysis, covariance estimation, statistical learning, and high-dimensional data analysis.;

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High Dimensional Econometrics and Identification

recovered even with noisy data in high-dimensional data, e.g., large panels. High-dimensional data in econometrics is the rule rather than the;

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Feature Selection for High-Dimensional Data

foundations, real application problems and the challenges of feature selection for high-dimensional data. The authors first focus on the analysis;

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Big Data in Omics and Imaging: Association Analysis

analysis, from low-dimensional to high dimensional, multivariate to functional data analysis with next-generation sequencing (NGS) data, and from;

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Big Data in Omics and Imaging: Association Analysis

-dimensional to high dimensional, multivariate to functional data analysis with next-generation sequencing (NGS) data, and from homogeneous populations;

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Survival Analysis in Medicine and Genetics

Using real data sets throughout, Survival Analysis in Medicine and Genetics introduces the latest methods for analyzing high-dimensional;

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Survival Analysis in Medicine and Genetics

Using real data sets throughout, Survival Analysis in Medicine and Genetics introduces the latest methods for analyzing high-dimensional;

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High Frequency Financial Econometrics

Shedding light on some of the most pressing open questions in the analysis of high frequency data, this volume presents cutting-edge;

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Functional and High-Dimensional Statistics and Related Fields

This book presents the latest research on the statistical analysis of functional, high-dimensional and other complex data, addressing;

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Big Data in Omics and Imaging, Two Volume Set

analysis and the modern advanced statistical methods for big data Provides tools for high dimensional data reduction Discusses searching;

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Applied Biclustering Methods for Big and High-Dimensional Data Using R

Biclustering Methods for Big and High-Dimensional Data Using R shows how to apply biclustering methods to find local patterns in a big data matrix;

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Time Series In High Dimensions

Factor models have become the most successful tool in the analysis and forecasting of high-dimensional time series. This monograph provides;

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High-Dimensional Covariance Matrix Estimation

that better fits the big data context. It draws attention to the deficiencies of standard statistical tools when used in the high-dimensional;

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High-dimensional Microarray Data Analysis

result is a 66-dimensional data. These signal data can be analyzed to find malignancy indicators by principal component analysis and cluster;

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Gaussian Process Regression Analysis for Functional Data

methodological developments for high dimensional data and variable selection. The remainder of the text explores advanced topics of functional regression;

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Spectral Analysis of Signals

astronomical time series analysis to synthetic aperture radar imaging with angular diversity. For spectral estimation in the missing-data case, the;

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Multivariate Time Series Analysis and Applications

, which may encourage the development of related software needed for the high dimensional multivariate time series analysis. Written by;

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Big Data Application in Power Systems

approaches to process high dimensional, heterogeneous and spatiotemporal data. The book chapters discuss challenges, opportunities, success stories;

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Nature Inspired Computing for Data Science

health care, object recognition, vehicular ad-hoc networking, high-dimensional data analysis, gene expression analysis, microgrids, and deep;

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