Linear Models And Regression With R An Integrated Approach
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Linear Models And Regression With R An Integrated Approach
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Author : Debasis Sengupta
language : en
Publisher: World Scientific
Release Date : 2019-07-30
Linear Models And Regression With R An Integrated Approach written by Debasis Sengupta and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-07-30 with Mathematics categories.
Starting with the basic linear model where the design and covariance matrices are of full rank, this book demonstrates how the same statistical ideas can be used to explore the more general linear model with rank-deficient design and/or covariance matrices. The unified treatment presented here provides a clearer understanding of the general linear model from a statistical perspective, thus avoiding the complex matrix-algebraic arguments that are often used in the rank-deficient case. Elegant geometric arguments are used as needed.The book has a very broad coverage, from illustrative practical examples in Regression and Analysis of Variance alongside their implementation using R, to providing comprehensive theory of the general linear model with 181 worked-out examples, 227 exercises with solutions, 152 exercises without solutions (so that they may be used as assignments in a course), and 320 up-to-date references.This completely updated and new edition of Linear Models: An Integrated Approach includes the following features:
Linear Models
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Author : Debasis Sengupta
language : en
Publisher: World Scientific
Release Date : 2003
Linear Models written by Debasis Sengupta and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003 with Mathematics categories.
Linear Models: An Integrated Approach aims to provide a clearand deep understanding of the general linear model using simplestatistical ideas. Elegant geometric arguments are also invoked asneeded and a review of vector spaces and matrices is provided to makethe treatment self-contained.
Data Science With R An Integrated Approach To Programming And Analytics
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Author : Prof.Lavanya.V
language : en
Publisher: Leilani Katie Publication
Release Date : 2025-05-07
Data Science With R An Integrated Approach To Programming And Analytics written by Prof.Lavanya.V and has been published by Leilani Katie Publication this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-07 with Computers categories.
Prof.Lavanya.V, Assistant Professor, Department of Computer Applications, CMR University, Bengaluru, Karnataka, India. Prof.N.Bhavyadevi Vishalakshi, Assistant Professor, Department of Computer Science and Engineering, CMR University, Bengaluru, Karnataka, India. Dr.T.Priya, Assistant Professor, Department of Computer Applications, East Point College of Higher Education, Bengaluru, Karnataka, India. Dr.S.Moses Praveen Mukharjee, Professor, Department of Computer Applications, East Point College of Higher Education, Bengaluru, Karnataka, India.
Linear Models In Statistics
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Author : Alvin C. Rencher
language : en
Publisher: John Wiley & Sons
Release Date : 2008-01-07
Linear Models In Statistics written by Alvin C. Rencher and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-01-07 with Mathematics categories.
The essential introduction to the theory and application of linear models—now in a valuable new edition Since most advanced statistical tools are generalizations of the linear model, it is neces-sary to first master the linear model in order to move forward to more advanced concepts. The linear model remains the main tool of the applied statistician and is central to the training of any statistician regardless of whether the focus is applied or theoretical. This completely revised and updated new edition successfully develops the basic theory of linear models for regression, analysis of variance, analysis of covariance, and linear mixed models. Recent advances in the methodology related to linear mixed models, generalized linear models, and the Bayesian linear model are also addressed. Linear Models in Statistics, Second Edition includes full coverage of advanced topics, such as mixed and generalized linear models, Bayesian linear models, two-way models with empty cells, geometry of least squares, vector-matrix calculus, simultaneous inference, and logistic and nonlinear regression. Algebraic, geometrical, frequentist, and Bayesian approaches to both the inference of linear models and the analysis of variance are also illustrated. Through the expansion of relevant material and the inclusion of the latest technological developments in the field, this book provides readers with the theoretical foundation to correctly interpret computer software output as well as effectively use, customize, and understand linear models. This modern Second Edition features: New chapters on Bayesian linear models as well as random and mixed linear models Expanded discussion of two-way models with empty cells Additional sections on the geometry of least squares Updated coverage of simultaneous inference The book is complemented with easy-to-read proofs, real data sets, and an extensive bibliography. A thorough review of the requisite matrix algebra has been addedfor transitional purposes, and numerous theoretical and applied problems have been incorporated with selected answers provided at the end of the book. A related Web site includes additional data sets and SAS® code for all numerical examples. Linear Model in Statistics, Second Edition is a must-have book for courses in statistics, biostatistics, and mathematics at the upper-undergraduate and graduate levels. It is also an invaluable reference for researchers who need to gain a better understanding of regression and analysis of variance.
Biostatistics With R A Guide For Medical Doctors
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Author : Marco Moscarelli
language : en
Publisher: Springer Nature
Release Date : 2023-08-14
Biostatistics With R A Guide For Medical Doctors written by Marco Moscarelli and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-08-14 with Medical categories.
This book aims not only to introduce fundamental biostatistics topics but to explain them through R-project (R-studio). 'R' is perhaps the more used statistical software in the medical field. It is structured as a 'scientific journey' and comes with a sham yet realistic dataset ready to be analysed. The dataset along with the R-script can be downloaded from GitHub, and each chapter has dedicated scripts that will enhance the understanding of R and biostatistics. Specifically designed for whoever works in the medical-academic environment, this practical guide will help the reader to become familiar with basic to advanced biostatistics topic (descriptive - analysis / regression etc.) and to gain solid knowledge of R.
A Course In Statistics With R
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Author : Prabhanjan N. Tattar
language : en
Publisher: John Wiley & Sons
Release Date : 2016-03-15
A Course In Statistics With R written by Prabhanjan N. Tattar and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-03-15 with Computers categories.
Integrates the theory and applications of statistics using R A Course in Statistics with R has been written to bridge the gap between theory and applications and explain how mathematical expressions are converted into R programs. The book has been primarily designed as a useful companion for a Masters student during each semester of the course, but will also help applied statisticians in revisiting the underpinnings of the subject. With this dual goal in mind, the book begins with R basics and quickly covers visualization and exploratory analysis. Probability and statistical inference, inclusive of classical, nonparametric, and Bayesian schools, is developed with definitions, motivations, mathematical expression and R programs in a way which will help the reader to understand the mathematical development as well as R implementation. Linear regression models, experimental designs, multivariate analysis, and categorical data analysis are treated in a way which makes effective use of visualization techniques and the related statistical techniques underlying them through practical applications, and hence helps the reader to achieve a clear understanding of the associated statistical models. Key features: Integrates R basics with statistical concepts Provides graphical presentations inclusive of mathematical expressions Aids understanding of limit theorems of probability with and without the simulation approach Presents detailed algorithmic development of statistical models from scratch Includes practical applications with over 50 data sets
Applied Linear Statistical Models
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Author : Michael H. Kutner
language : en
Publisher: McGraw-Hill Education
Release Date : 2005
Applied Linear Statistical Models written by Michael H. Kutner and has been published by McGraw-Hill Education this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005 with Analysis of variance categories.
Applied Linear Statistical Models 5e is the long established leading authoritative text and reference on statistical modeling. For students in most any discipline where statistical analysis or interpretation is used, ALSM serves as the standard work. The text includes brief introductory and review material, and then proceeds through regression and modeling for the first half, and through ANOVA and Experimental Design in the second half. All topics are presented in a precise and clear style supported with solved examples, numbered formulae, graphic illustrations, and "Notes" to provide depth and statistical accuracy and precision. Applications used within the text and the hallmark problems, exercises, and projects are drawn from virtually all disciplines and fields providing motivation for students in virtually any college. The Fifth edition provides an increased use of computing and graphical analysis throughout, without sacrificing concepts or rigor. In general, the 5e uses larger data sets in examples and exercises, and where methods can be automated within software without loss of understanding, it is so done.
Learning Statistics With R
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Author : Danielle Navarro
language : en
Publisher:
Release Date : 2018
Learning Statistics With R written by Danielle Navarro and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018 with categories.
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 techniques described in the book. This book is suitable for graduate students who are either majoring in statistics/biostatistics or using linear regression analysis substantially in their subject area." --Book Jacket.
Hilbert And Banach Space Valued Stochastic Processes
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Author : Yuichiro Kakihara
language : en
Publisher: World Scientific
Release Date : 2021-07-29
Hilbert And Banach Space Valued Stochastic Processes written by Yuichiro Kakihara and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-07-29 with Mathematics categories.
This is a development of the book entitled Multidimensional Second Order Stochastic Processes. It provides a research expository treatment of infinite-dimensional stationary and nonstationary stochastic processes or time series, based on Hilbert and Banach space-valued second order random variables. Stochastic measures and scalar or operator bimeasures are fully discussed to develop integral representations of various classes of nonstationary processes such as harmonizable, V-bounded, Cramér and Karhunen classes as well as the stationary class. A new type of the Radon-Nikodým derivative of a Banach space-valued measure is introduced, together with Schauder basic measures, to study uniformly bounded linearly stationary processes.Emphasis is on the use of functional analysis and harmonic analysis as well as probability theory. Applications are made from the probabilistic and statistical points of view to prediction problems, Kalman filter, sampling theorems and strong laws of large numbers. Generalizations are made to consider Banach space-valued stochastic processes to include processes of pth order for p ≥ 1. Readers may find that the covariance kernel is always emphasized and reveals another aspect of stochastic processes.This book is intended not only for probabilists and statisticians, but also for functional analysts and communication engineers.