Circular And Linear Regression


Circular And Linear Regression
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Circular And Linear Regression


Circular And Linear Regression
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Author : Nikolai Chernov
language : en
Publisher: CRC Press
Release Date : 2010-06-22

Circular And Linear Regression written by Nikolai Chernov and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-06-22 with Computers categories.


Find the right algorithm for your image processing applicationExploring the recent achievements that have occurred since the mid-1990s, Circular and Linear Regression: Fitting Circles and Lines by Least Squares explains how to use modern algorithms to fit geometric contours (circles and circular arcs) to observed data in image processing and comput



Topics In Circular Statistics


Topics In Circular Statistics
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Author : S. Rao Jammalamadaka
language : en
Publisher: World Scientific
Release Date : 2001

Topics In Circular Statistics written by S. Rao Jammalamadaka and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001 with Mathematics categories.


This research monograph on circular data analysis covers some recent advances in the field, besides providing a brief introduction to, and a review of, existing methods and models. The primary focus is on recent research into topics such as change-point problems, predictive distributions, circular correlation and regression, etc. An important feature of this work is the S-plus subroutines provided for analyzing actual data sets. Coupled with the discussion of new theoretical research, the book should benefit both the researcher and the practitioner.



Linear Regression Analysis


Linear Regression Analysis
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Author : Xin Yan
language : en
Publisher: World Scientific
Release Date : 2009

Linear Regression Analysis written by Xin Yan and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009 with Mathematics categories.


This volume presents in detail the fundamental theories of linear regression analysis and diagnosis, as well as the relevant statistical computing techniques so that readers are able to actually model the data using the methods and techniques described in the book. It covers the fundamental theories in linear regression analysis and is extremely useful for future research in this area. The examples of regression analysis using the Statistical Application System (SAS) are also included. This book is suitable for graduate students who are either majoring in statistics/biostatistics or using linear regression analysis substantially in their subject fields.



Statistics And Its Applications


Statistics And Its Applications
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Author : Asis Kumar Chattopadhyay
language : en
Publisher: Springer
Release Date : 2018-08-16

Statistics And Its Applications written by Asis Kumar Chattopadhyay and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-08-16 with Mathematics categories.


This book discusses recent developments and the latest research in statistics and its applications, primarily in agriculture and industry, survey sampling and biostatistics, gathering articles on a wide variety of topics. Written by leading academics, scientists, researchers and scholars from around the globe to mark the platinum jubilee of the Department of Statistics, University of Calcutta in 2016, the book is a valuable resource for statisticians, aspiring researchers and professionals across educational levels and disciplines.



Modern Directional Statistics


Modern Directional Statistics
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Author : Christophe Ley
language : en
Publisher: CRC Press
Release Date : 2017-08-03

Modern Directional Statistics written by Christophe Ley and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-08-03 with Computers categories.


Modern Directional Statistics collects important advances in methodology and theory for directional statistics over the last two decades. It provides a detailed overview and analysis of recent results that can help both researchers and practitioners. Knowledge of multivariate statistics eases the reading but is not mandatory. The field of directional statistics has received a lot of attention over the past two decades, due to new demands from domains such as life sciences or machine learning, to the availability of massive data sets requiring adapted statistical techniques, and to technological advances. This book covers important progresses in distribution theory,high-dimensional statistics, kernel density estimation, efficient inference on directional supports, and computational and graphical methods. Christophe Ley is professor of mathematical statistics at Ghent University. His research interests include semi-parametrically efficient inference, flexible modeling, directional statistics and the study of asymptotic approximations via Stein’s Method. His achievements include the Marie-Jeanne Laurent-Duhamel prize of the Société Française de Statistique and an elected membership at the International Statistical Institute. He is associate editor for the journals Computational Statistics & Data Analysis and Econometrics and Statistics. Thomas Verdebout is professor of mathematical statistics at Université libre de Bruxelles (ULB). His main research interests are semi-parametric statistics, high- dimensional statistics, directional statistics and rank-based procedures. He has won an annual prize of the Belgian Academy of Sciences and is an elected member of the International Statistical Institute. He is associate editor for the journals Statistics and Probability Letters and Journal of Multivariate Analysis.



Circular Statistical Methods


Circular Statistical Methods
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Author : Robert Peter Mahan
language : en
Publisher:
Release Date : 1991

Circular Statistical Methods written by Robert Peter Mahan and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1991 with Performance categories.




Mathematical Algorithms For Linear Regression


Mathematical Algorithms For Linear Regression
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Author : Helmuth Späth
language : en
Publisher:
Release Date : 1992

Mathematical Algorithms For Linear Regression written by Helmuth Späth and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1992 with Mathematics categories.




Nonlinear Regression With R


Nonlinear Regression With R
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Author : Christian Ritz
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-12-11

Nonlinear Regression With R written by Christian Ritz and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-12-11 with Mathematics categories.


- Coherent and unified treatment of nonlinear regression with R. - Example-based approach. - Wide area of application.



Handbook Of Regression Methods


Handbook Of Regression Methods
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Author : Derek Scott Young
language : en
Publisher: CRC Press
Release Date : 2018-10-03

Handbook Of Regression Methods written by Derek Scott Young and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-10-03 with Mathematics categories.


Handbook of Regression Methods concisely covers numerous traditional, contemporary, and nonstandard regression methods. The handbook provides a broad overview of regression models, diagnostic procedures, and inference procedures, with emphasis on how these methods are applied. The organization of the handbook benefits both practitioners and researchers, who seek either to obtain a quick understanding of regression methods for specialized problems or to expand their own breadth of knowledge of regression topics. This handbook covers classic material about simple linear regression and multiple linear regression, including assumptions, effective visualizations, and inference procedures. It presents an overview of advanced diagnostic tests, remedial strategies, and model selection procedures. Finally, many chapters are devoted to a diverse range of topics, including censored regression, nonlinear regression, generalized linear models, and semiparametric regression. Features Presents a concise overview of a wide range of regression topics not usually covered in a single text Includes over 80 examples using nearly 70 real datasets, with results obtained using R Offers a Shiny app containing all examples, thus allowing access to the source code and the ability to interact with the analyses



Intracranial Eeg


Intracranial Eeg
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Author : Nikolai Axmacher
language : en
Publisher: Springer Nature
Release Date : 2023-08-01

Intracranial Eeg written by Nikolai Axmacher and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-08-01 with Technology & Engineering categories.


This book offers the first, comprehensive guide to planning and conducting intracranial EEG studies, and analyzing intracranial EEG data. The chapters address core questions in the field of intracranial EEG research. They are written by internationally recognized experts in the domain of intracranial EEG and acknowledge the heterogeneity of approaches in this field. The particular format of the book allows readers to find clear guidelines, hands-on expertise and invaluable background information for planning and conducting state-of-the-art intracranial EEG research projects. Besides offering a reference guide to newcomers in the field, it also provides scholarly information for the more experienced researcher and inspiration for the expert. The book covers a wide range of topics, with a special emphasis on aspects in which intracranial EEG data differ from other types of data in the cognitive neurosciences. It discusses typical patient characteristics and implantation schemes, ethical issues, and practical considerations for planning and running intracranial EEG experiments. It addresses signal characteristics and the physiological background of oscillatory and non-oscillatory aspects of intracranial EEG signals. It describes complex pre-processing steps such as advantages and disadvantages of different referencing schemes, and how to identify the location of electrodes. In addition, it answers specific questions on data processing, addressing core aspects of statistical analysis, and suggesting guidelines for data presentation. Further, it covers advanced topics such as causal interventions (i.e. deep brain stimulation), acquisition and analysis of single-unit data and multimodal recordings, and discusses important future challenges and opportunities in the field of intracranial EEG research.