Statistical and Multivariate Analysis in Material Science, Giorgio Luciano
Автор: Trevor Hastie; Robert Tibshirani; Jerome Friedman Название: The Elements of Statistical Learning ISBN: 0387848576 ISBN-13(EAN): 9780387848570 Издательство: Springer Рейтинг: Цена: 10480.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This major new edition features many topics not covered in the original, including graphical models, random forests, and ensemble methods. As before, it covers the conceptual framework for statistical data in our rapidly expanding computerized world.
Автор: Giorgio Luciano (Editor) Название: Statistical And Multivariate Analys ISBN: 1138196304 ISBN-13(EAN): 9781138196308 Издательство: Taylor&Francis Рейтинг: Цена: 16078.00 р. 22968.00-30% Наличие на складе: Есть (1 шт.) Описание: The present work is an introductory text in statistics, addressed to researchers and students in the field of material science. It aims to give the readers basic knowledge on how statistical reasoning is exploitable in this field, improving their knowledge of statistical tools.
Автор: Montesinos Lуpez Osval Antonio, Montesinos Lуpez Abelardo, Crossa Josй Название: Multivariate Statistical Machine Learning Methods for Genomic Prediction ISBN: 3030890120 ISBN-13(EAN): 9783030890124 Издательство: Springer Рейтинг: Цена: 5589.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: It provides an accessible way to understand the theory behind each statistical learning tool, the required pre-processing, the basics of model building, how to train statistical learning methods, the basic R scripts needed to implement each statistical learning tool, and the output of each tool.
Автор: Montesinos Lуpez Osval Antonio, Montesinos Lуpez Abelardo, Crossa Josй Название: Multivariate Statistical Machine Learning Methods for Genomic Prediction ISBN: 3030890090 ISBN-13(EAN): 9783030890094 Издательство: Springer Рейтинг: Цена: 5589.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: It provides an accessible way to understand the theory behind each statistical learning tool, the required pre-processing, the basics of model building, how to train statistical learning methods, the basic R scripts needed to implement each statistical learning tool, and the output of each tool.
Автор: Milena Lakicevic, Nicholas Povak, Keith M. Reynold Название: Introduction to R for Terrestrial Ecology ISBN: 3030276023 ISBN-13(EAN): 9783030276027 Издательство: Springer Рейтинг: Цена: 8384.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
This textbook covers R data analysis related to environmental science, starting with basic examples and proceeding up to advanced applications of the R programming language. The main objective of the textbook is to serve as a guide for undergraduate students, who have no previous experience with R, but part of the textbook is dedicated to advanced R applications, and will also be useful for Masters and PhD students, and professionals.
The textbook deals with solving specific programming tasks in R, and tasks are organized in terms of gradually increasing R proficiency, with examples getting more challenging as the chapters progress. The main competencies students will acquire from this textbook are:
manipulating and processing data tables
performing statistical tests
creating maps in R
This textbook will be useful in undergraduate and graduate courses in Advanced Landscape Ecology, Analysis of Ecological and Environmental Data, Ecological Modeling, Analytical Methods for Ecologists, Statistical Inference for Applied Research, Elements of Statistical Methods, Computational Ecology, Landscape Metrics and Spatial Statistics.
Описание: This book offers comprehensive information on the theory, models and algorithms involved in state-of-the-art multivariate time series analysis and highlights several of the latest research advances in climate and environmental science. The main topics addressed include Multivariate Time-Frequency Analysis, Artificial Neural Networks, Stochastic Modeling and Optimization, Spectral Analysis, Global Climate Change, Regional Climate Change, Ecosystem and Carbon Cycle, Paleoclimate, and Strategies for Climate Change Mitigation. The self-contained guide will be of great value to researchers and advanced students from a wide range of disciplines: those from Meteorology, Climatology, Oceanography, the Earth Sciences and Environmental Science will be introduced to various advanced tools for analyzing multivariate data, greatly facilitating their research, while those from Applied Mathematics, Statistics, Physics, and the Computer Sciences will learn how to use these multivariate time series analysis tools to approach climate and environmental topics.
Описание: This book offers comprehensive information on the theory, models and algorithms involved in state-of-the-art multivariate time series analysis and highlights several of the latest research advances in climate and environmental science. The main topics addressed include Multivariate Time-Frequency Analysis, Artificial Neural Networks, Stochastic Modeling and Optimization, Spectral Analysis, Global Climate Change, Regional Climate Change, Ecosystem and Carbon Cycle, Paleoclimate, and Strategies for Climate Change Mitigation. The self-contained guide will be of great value to researchers and advanced students from a wide range of disciplines: those from Meteorology, Climatology, Oceanography, the Earth Sciences and Environmental Science will be introduced to various advanced tools for analyzing multivariate data, greatly facilitating their research, while those from Applied Mathematics, Statistics, Physics, and the Computer Sciences will learn how to use these multivariate time series analysis tools to approach climate and environmental topics.
Автор: J. Devillers; W. Karcher Название: Applied Multivariate Analysis in SAR and Environmental Studies ISBN: 940105410X ISBN-13(EAN): 9789401054102 Издательство: Springer Рейтинг: Цена: 13974.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Based on the Lectures given during the Eurocourse on `Applied Multivariate Analysis in SAR and Environmental Studies` held at the Joint Research Centre, Ispra, Italy, June 24-28, 1991
Автор: B.B. Manly; L. McDonald; D.L. Thomas Название: Resource Selection by Animals ISBN: 9401046808 ISBN-13(EAN): 9789401046800 Издательство: Springer Рейтинг: Цена: 22203.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: We have written this book as a guide to the design and analysis of field studies of resource selection, concentrating primarily on statistical aspects of the comparison of the use and availability of resources of different types.
Автор: F.J. Fahy; W.G. Price Название: IUTAM Symposium on Statistical Energy Analysis ISBN: 0792354575 ISBN-13(EAN): 9780792354574 Издательство: Springer Рейтинг: Цена: 47377.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Presents the proceedings of the IUTAM Symposium on Statistical Energy Analysis, the first international symposium specifically devoted to a method of vibration analysis. This title provides academics, engineers and consultants with a comprehensive survey of the Statistical Energy Analysis (SEA).
Описание: This text deals with a new technique for the dynamic analysis of nonlinear structures, which allows engineers to deal with complex nonlinear problems in a systematic manner. It is especially relevant in dealing with offshore structures which are exposed to nonlinear forces due to waves.
Описание: This book presents an overview of computational and statistical design and analysis of mass spectrometry-based proteomics, metabolomics, and lipidomics data. This contributed volume provides an introduction to the special aspects of statistical design and analysis with mass spectrometry data for the new omic sciences. The text discusses common aspects of design and analysis between and across all (or most) forms of mass spectrometry, while also providing special examples of application with the most common forms of mass spectrometry. Also covered are applications of computational mass spectrometry not only in clinical study but also in the interpretation of omics data in plant biology studies.Omics research fields are expected to revolutionize biomolecular research by the ability to simultaneously profile many compounds within either patient blood, urine, tissue, or other biological samples. Mass spectrometry is one of the key analytical techniques used in these new omic sciences. Liquid chromatography mass spectrometry, time-of-flight data, and Fourier transform mass spectrometry are but a selection of the measurement platforms available to the modern analyst. Thus in practical proteomics or metabolomics, researchers will not only be confronted with new high dimensional data types—as opposed to the familiar data structures in more classical genomics—but also with great variation between distinct types of mass spectral measurements derived from different platforms, which may complicate analyses, comparison, and interpretation of results.
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