Applied Multivariate Statistics In Geohydrology And Related Sciences

Download Applied Multivariate Statistics In Geohydrology And Related Sciences PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Applied Multivariate Statistics In Geohydrology And Related Sciences book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages.
Applied Multivariate Statistics in Geohydrology and Related Sciences

Author: Charles E. Brown
language: en
Publisher: Springer Science & Business Media
Release Date: 2012-12-06
It has been evident from many years of research work in the geohydrologic sciences that a summary of relevant past work, present work, and needed future work in multivariate statistics with geohydrologic applications is not only desirable, but is necessary. This book is intended to serve a broad scientific audience, but more specifi cally is geared toward scientists doing studies in geohydrology and related geo sciences.lts objective is to address both introductory and advanced concepts and applications of the multivariate procedures in use today. Some of the procedures are classical in scope but others are on the forefront of statistical science and have received limited use in geohydrology or related sciences. The past three decades have seen a significant jump in the application of new research methodologies that focus on analyzing large databases. With more general applications being developed by statisticians in various disciplines, multivariate quantitative procedures are evolving for better scientific applica tion at a rapid rate and now provide for quick and informative analyses of large datasets. The procedures include a family of statistical research methods that are alternatively called "multivariate analysis" or "multivariate statistical methods".
Python Recipes for Earth Sciences

Python is used in a wide range of geoscientific applications, such as in processing images for remote sensing, in generating and processing digital elevation models, and in analyzing time series. This book introduces methods of data analysis in the geosciences using Python that include basic statistics for univariate, bivariate, and multivariate data sets, time series analysis, and signal processing; the analysis of spatial and directional data; and image analysis. The text includes numerous examples that demonstrate how Python can be used on data sets from the earth sciences. The supplementary electronic material (available online through Springer Link) contains the example data as well as recipes that include all the Python commands featured in the book.
MATLAB® Recipes for Earth Sciences

MATLAB® is used in a wide range of geoscientific applications, e.g. for image processing in remote sensing, for creating and processing digital elevation models, and for analyzing time series. This book introduces readers to MATLAB-based data analysis methods used in the geosciences, including basic statistics for univariate, bivariate and multivariate datasets, time-series analysis, signal processing, the analysis of spatial and directional data, and image analysis. The revised and updated Fifth Edition includes seven new sections, and the majority of the chapters have been rewritten and significantly expanded. New sections include error analysis, the problem of classical linear regression of log-transformed data, aligning stratigraphic sequences, the Normalized Difference Vegetation Index, Aitchison’s log-ratio transformation, graphical representation of spherical data, and statistics of spherical data. The book also includes numerous examples demonstrating how MATLAB can be used on datasets from the earth sciences. The supplementary electronic material (available online through SpringerLink) contains recipes that include all the MATLAB commands featured in the book and the sample data.