Introduction To Uses And Interpretation Of Principal Component Analysis In Forest Biology Classic Reprint

Author : J. G. Isebrands
Publisher : Forgotten Books
Page : 990 pages
File Size : 47,6 Mb
Release : 2017-11-05
Category : Business & Economics
ISBN : 0265111226

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Introduction to Uses and Interpretation of Principal Component Analysis in Forest Biology (Classic Reprint) by J. G. Isebrands Pdf

Excerpt from Introduction to Uses and Interpretation of Principal Component Analysis in Forest Biology Our objective is to introduce pca to the forest biologist. Who has had an expo sure to introductory statistics, and likely applies anova, correlation, and regression routinely, but who has not made the jump to multivariate techniques. Our intent is to demonstrate through detailed examination of two applications the utility of princi pal component analysis in helping solve re search problems in forest biology. About the Publisher Forgotten Books publishes hundreds of thousands of rare and classic books. Find more at www.forgottenbooks.com This book is a reproduction of an important historical work. Forgotten Books uses state-of-the-art technology to digitally reconstruct the work, preserving the original format whilst repairing imperfections present in the aged copy. In rare cases, an imperfection in the original, such as a blemish or missing page, may be replicated in our edition. We do, however, repair the vast majority of imperfections successfully; any imperfections that remain are intentionally left to preserve the state of such historical works.

Author : Judson Gary Isebrands,Thomas R. Crow
Publisher : Unknown
Page : 984 pages
File Size : 52,8 Mb
Release : 1975
Category : Forests and forestry
ISBN : STANFORD:36105005951160

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Introduction to Uses and Interpretation of Principal Component Analysis in Forest Biology by Judson Gary Isebrands,Thomas R. Crow Pdf

Author : Anonim
Publisher : Unknown
Page : 848 pages
File Size : 45,9 Mb
Release : 1976
Category : Government reports announcements & index
ISBN : MINN:319510006566265

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Government Reports Annual Index by Anonim Pdf

Author : Brian L. Murphy,Robert D. Morrison
Publisher : Academic Press
Page : 747 pages
File Size : 52,6 Mb
Release : 2014-07-30
Category : Science
ISBN : 9780124047075

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Introduction to Environmental Forensics by Brian L. Murphy,Robert D. Morrison Pdf

The third edition of Introduction to Environmental Forensics is a state-of-the-art reference for the practicing environmental forensics consultant, regulator, student, academic, and scientist, with topics including compound-specific isotope analysis (CSIA), advanced multivariate statistical techniques, surrogate approaches for contaminant source identification and age dating, dendroecology, hydrofracking, releases from underground storage tanks and piping, and contaminant-transport modeling for forensic applications. Recognized international forensic scientists were selected to author chapters in their specific areas of expertise and case studies are included to illustrate the application of these methods in actual environmental forensic investigations. This edition provides updates on advances in various techniques and introduces several new topics. Provides a comprehensive review of all aspects of environmental forensics Coverage ranges from emerging statistical methods to state-of-the-art analytical techniques, such as gas chromatography-combustion-isotope ratio mass spectrometry and polytopic vector analysis Numerous examples and case studies are provided to illustrate the application of these forensic techniques in environmental investigations

Author : Peter Bruce,Andrew Bruce
Publisher : "O'Reilly Media, Inc."
Page : 395 pages
File Size : 44,7 Mb
Release : 2017-05-10
Category : Computers
ISBN : 9781491952917

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Practical Statistics for Data Scientists by Peter Bruce,Andrew Bruce Pdf

Statistical methods are a key part of of data science, yet very few data scientists have any formal statistics training. Courses and books on basic statistics rarely cover the topic from a data science perspective. This practical guide explains how to apply various statistical methods to data science, tells you how to avoid their misuse, and gives you advice on what's important and what's not. Many data science resources incorporate statistical methods but lack a deeper statistical perspective. If you’re familiar with the R programming language, and have some exposure to statistics, this quick reference bridges the gap in an accessible, readable format. With this book, you’ll learn: Why exploratory data analysis is a key preliminary step in data science How random sampling can reduce bias and yield a higher quality dataset, even with big data How the principles of experimental design yield definitive answers to questions How to use regression to estimate outcomes and detect anomalies Key classification techniques for predicting which categories a record belongs to Statistical machine learning methods that “learn” from data Unsupervised learning methods for extracting meaning from unlabeled data

Author : Alain Zuur,Elena N. Ieno,Graham M. Smith
Publisher : Springer
Page : 686 pages
File Size : 46,7 Mb
Release : 2007-08-29
Category : Science
ISBN : 9780387459721

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Analyzing Ecological Data by Alain Zuur,Elena N. Ieno,Graham M. Smith Pdf

This book provides a practical introduction to analyzing ecological data using real data sets. The first part gives a largely non-mathematical introduction to data exploration, univariate methods (including GAM and mixed modeling techniques), multivariate analysis, time series analysis, and spatial statistics. The second part provides 17 case studies. The case studies include topics ranging from terrestrial ecology to marine biology and can be used as a template for a reader’s own data analysis. Data from all case studies are available from www.highstat.com. Guidance on software is provided in the book.

Author : Gerald Peter Quinn,Michael J. Keough
Publisher : Cambridge University Press
Page : 560 pages
File Size : 44,7 Mb
Release : 2002-03-21
Category : Mathematics
ISBN : 0521009766

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Experimental Design and Data Analysis for Biologists by Gerald Peter Quinn,Michael J. Keough Pdf

Regression, analysis of variance, correlation, graphical.

Author : F. Halle,R.A.A. Oldeman,P.B. Tomlinson
Publisher : Springer Science & Business Media
Page : 457 pages
File Size : 48,7 Mb
Release : 2012-12-06
Category : Science
ISBN : 9783642811906

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Tropical Trees and Forests by F. Halle,R.A.A. Oldeman,P.B. Tomlinson Pdf

Author : Samantha Fowler,Rebecca Roush,James Wise
Publisher : Unknown
Page : 618 pages
File Size : 46,8 Mb
Release : 2018-01-07
Category : Science
ISBN : 9888407457

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Concepts of Biology by Samantha Fowler,Rebecca Roush,James Wise Pdf

Concepts of Biology is designed for the single-semester introduction to biology course for non-science majors, which for many students is their only college-level science course. As such, this course represents an important opportunity for students to develop the necessary knowledge, tools, and skills to make informed decisions as they continue with their lives. Rather than being mired down with facts and vocabulary, the typical non-science major student needs information presented in a way that is easy to read and understand. Even more importantly, the content should be meaningful. Students do much better when they understand why biology is relevant to their everyday lives. For these reasons, Concepts of Biology is grounded on an evolutionary basis and includes exciting features that highlight careers in the biological sciences and everyday applications of the concepts at hand.We also strive to show the interconnectedness of topics within this extremely broad discipline. In order to meet the needs of today's instructors and students, we maintain the overall organization and coverage found in most syllabi for this course. A strength of Concepts of Biology is that instructors can customize the book, adapting it to the approach that works best in their classroom. Concepts of Biology also includes an innovative art program that incorporates critical thinking and clicker questions to help students understand--and apply--key concepts.

Author : Brad Boehmke,Brandon M. Greenwell
Publisher : CRC Press
Page : 374 pages
File Size : 49,9 Mb
Release : 2019-11-07
Category : Business & Economics
ISBN : 9781000730432

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Hands-On Machine Learning with R by Brad Boehmke,Brandon M. Greenwell Pdf

Hands-on Machine Learning with R provides a practical and applied approach to learning and developing intuition into today’s most popular machine learning methods. This book serves as a practitioner’s guide to the machine learning process and is meant to help the reader learn to apply the machine learning stack within R, which includes using various R packages such as glmnet, h2o, ranger, xgboost, keras, and others to effectively model and gain insight from their data. The book favors a hands-on approach, providing an intuitive understanding of machine learning concepts through concrete examples and just a little bit of theory. Throughout this book, the reader will be exposed to the entire machine learning process including feature engineering, resampling, hyperparameter tuning, model evaluation, and interpretation. The reader will be exposed to powerful algorithms such as regularized regression, random forests, gradient boosting machines, deep learning, generalized low rank models, and more! By favoring a hands-on approach and using real word data, the reader will gain an intuitive understanding of the architectures and engines that drive these algorithms and packages, understand when and how to tune the various hyperparameters, and be able to interpret model results. By the end of this book, the reader should have a firm grasp of R’s machine learning stack and be able to implement a systematic approach for producing high quality modeling results. Features: · Offers a practical and applied introduction to the most popular machine learning methods. · Topics covered include feature engineering, resampling, deep learning and more. · Uses a hands-on approach and real world data.

Author : Julian P. T. Higgins,Sally Green
Publisher : Wiley
Page : 672 pages
File Size : 55,5 Mb
Release : 2008-11-24
Category : Medical
ISBN : 0470699515

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Cochrane Handbook for Systematic Reviews of Interventions by Julian P. T. Higgins,Sally Green Pdf

Healthcare providers, consumers, researchers and policy makers are inundated with unmanageable amounts of information, including evidence from healthcare research. It has become impossible for all to have the time and resources to find, appraise and interpret this evidence and incorporate it into healthcare decisions. Cochrane Reviews respond to this challenge by identifying, appraising and synthesizing research-based evidence and presenting it in a standardized format, published in The Cochrane Library (www.thecochranelibrary.com). The Cochrane Handbook for Systematic Reviews of Interventions contains methodological guidance for the preparation and maintenance of Cochrane intervention reviews. Written in a clear and accessible format, it is the essential manual for all those preparing, maintaining and reading Cochrane reviews. Many of the principles and methods described here are appropriate for systematic reviews applied to other types of research and to systematic reviews of interventions undertaken by others. It is hoped therefore that this book will be invaluable to all those who want to understand the role of systematic reviews, critically appraise published reviews or perform reviews themselves.

Author : Jan Lepš,Petr Šmilauer
Publisher : Cambridge University Press
Page : 296 pages
File Size : 43,5 Mb
Release : 2003-05-29
Category : Computers
ISBN : 0521891086

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Multivariate Analysis of Ecological Data Using CANOCO by Jan Lepš,Petr Šmilauer Pdf

Table of contents

Author : Gareth James,Daniela Witten,Trevor Hastie,Robert Tibshirani,Jonathan Taylor
Publisher : Springer Nature
Page : 617 pages
File Size : 45,9 Mb
Release : 2023-08-01
Category : Mathematics
ISBN : 9783031387470

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An Introduction to Statistical Learning by Gareth James,Daniela Witten,Trevor Hastie,Robert Tibshirani,Jonathan Taylor Pdf

An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance, marketing, and astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, deep learning, survival analysis, multiple testing, and more. Color graphics and real-world examples are used to illustrate the methods presented. This book is targeted at statisticians and non-statisticians alike, who wish to use cutting-edge statistical learning techniques to analyze their data. Four of the authors co-wrote An Introduction to Statistical Learning, With Applications in R (ISLR), which has become a mainstay of undergraduate and graduate classrooms worldwide, as well as an important reference book for data scientists. One of the keys to its success was that each chapter contains a tutorial on implementing the analyses and methods presented in the R scientific computing environment. However, in recent years Python has become a popular language for data science, and there has been increasing demand for a Python-based alternative to ISLR. Hence, this book (ISLP) covers the same materials as ISLR but with labs implemented in Python. These labs will be useful both for Python novices, as well as experienced users.

Author : Soil Science Society of America
Publisher : Unknown
Page : 1104 pages
File Size : 45,8 Mb
Release : 1974
Category : Soil science
ISBN : STANFORD:36105007681518

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Proceedings by Soil Science Society of America Pdf

Author : Shai Shalev-Shwartz,Shai Ben-David
Publisher : Cambridge University Press
Page : 415 pages
File Size : 49,8 Mb
Release : 2014-05-19
Category : Computers
ISBN : 9781107057135

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Understanding Machine Learning by Shai Shalev-Shwartz,Shai Ben-David Pdf

Introduces machine learning and its algorithmic paradigms, explaining the principles behind automated learning approaches and the considerations underlying their usage.