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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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Big Data in Omics and Imaging: Association Analysis

advanced statistical methods for big data Provides tools for high dimensional data reduction Discusses searching algorithms for model;

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Big Data in Omics and Imaging: Association Analysis

advanced statistical methods for big data Provides tools for high dimensional data reduction Discusses searching algorithms for model and;

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Applied Compositional Data Analysis

, classification and regression. In addition, it considers special data structures like high-dimensional compositions and compositional tables. The;

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Recent Advances in Theory and Methods for the Analysis of High Dimensional and High Frequency Financial Data

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

High-Dimensional Data, Second Edition is also a useful text for graduate-level courses on statistics, computational biology, and bioinformatics.;

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Handbook of Big Data Analytics

is primarily intended for statisticians, computer experts, engineers and application developers interested in using big data analytics with statistics;

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Handbook of Big Data Analytics

is primarily intended for statisticians, computer experts, engineers and application developers interested in using big data analytics with statistics;

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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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Test Data Engineering

structure within the data to be visualized, and thereby make test results useful for students, teachers, and the society. The author does not;

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Analyzing High-Dimensional Gene Expression and DNA Methylation Data with R

Analyzing high-dimensional gene expression and DNA methylation data with R is the first practical book that shows a ``pipeline;

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Analyzing High-Dimensional Gene Expression and DNA Methylation Data with R

Analyzing high-dimensional gene expression and DNA methylation data with R is the first practical book that shows a ``pipeline;

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Principles and Methods for Data Science

Data with High Dimension, High dimensional statistical inference: theoretical development to data analytics, Big data challenges in genomics;

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Spectral Clustering And Biclustering

are presented together with the theoretical background and proofs. This book is suitable for a one-semester course for graduate students;

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Nonparametric Statistical Methods Using R

methods with many real and simulated data examples using R, including the packages Rfit and npsm. The book first gives an overview of the R;

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Nonparametric Statistical Methods Using R

. They illustrate the methods with many real and simulated data examples using R, including the packages Rfit and npsm. The book first;

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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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Statistics for High-Dimensional Data

comprehensive mathematical theory on high-dimensional statistics combined with methodology, algorithms and illustrations with real data examples. This;

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Statistics for High-Dimensional Data

comprehensive mathematical theory on high-dimensional statistics combined with methodology, algorithms and illustrations with real data examples. This;

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Spatial Analysis Using Big Data

Spatial Analysis Using Big Data: Methods and Urban Applications helps readers understand the most powerful, state-of-the-art spatial;

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Qualitative and Mixed Methods Data Analysis Using Dedoose

Qualitative and Mixed Methods Data Analysis Using Dedoose (R): A Practical Approach for Research Across the Social Sciences provides both;

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Learn R for Applied Statistics

Is For Those who are interested in data science, in particular data exploration using applied statistics, and the use of R programming for data;

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Analysis Of Multivariate & High Dimensio

methods with small classical data, data from medicine, biology, marketing and finance, high-dimensional data from bioinformatics, functional data;

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Big Data Meets Survey Science

Offers a clear view of the utility and place for survey data within the broader Big Data ecosystem This book presents a collection;

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Learning Bayesian Models with R: Become an expert in Bayesian Machine Learning methods using R and apply them to solve real-world big data problems

Become an expert in Bayesian Machine Learning methods using R and apply them to solve real-world big data problems About This Book;

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Big Data Application in Power Systems

, measurement data availability, big data handling and machine learning approaches to process high dimensional, heterogeneous and spatiotemporal data;

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Bayesian Statistical Methods

Handling of missing data using predictive distributions Priors for high-dimensional regression models;

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