Linear Mixed-Effects Models Using R

Describes the racial prejudice experienced by Jackie Robinson when he joined the Brooklyn Dodgers and became the first black player in Major League baseball and depicts the acceptance and support he r

ntroduction and Notes by Dr Jeff Wallace, University of Glamorgan.Lawrence's finest, most mature novel initially met with disgust and incomprehension. In the love affairs of two sisters, Ursula with R

During the eighteenth century, China's new Manchu rulers consolidated their control of the largest empire China had ever known. In this book Susan Naquin and Evelyn S. Rawski draw on the most recent r

十二歲的克勞蒂雅為了讓爸媽重視自己，決定離家出走，躲進大都會博物館。她帶著弟弟一起，卻在館內發現一尊神祕雕像，決心查出它的真相。這部小說結合博物館探險、輕鬆推理與成長觀察，是紐伯瑞獎經典之作，至今仍深受讀者喜愛。A Time Best YA Book of All Time (2021)Run away to the Metropolitan Museum of Art with E. L. Konigsburg’s beloved classic and Newbery Medal­–winning novel From the Mixed-Up Files of Mrs. Basil E. Frankweiler!When Claudia decided to run away, she planned very carefully. She would be gone just long enough to teach her parents a lesson in Claudia appreciation. And she would go in comfort-she would live at the Metropolitan Museum of Art. She saved her money, and she invited her brother Jamie to go, mostly because be was a miser and would have money.Claudia was a good organizer and Jamie bad some ideas, too; so the two took up residence at the museum right on schedule. But once the fun of settling in was over, Claudia had two unexpected problems: She felt just the same, and she wanted to feel different; and she found a statue at the Museum so beautiful she could not go home until she

An illustrated rhyming biography of the African American woman and first Naval engineer to design a ship using a computer. “Solid inspiration.” -Kirkus, starred review

1. JYbooks' Company Song 2. Story Reading 3. Story Reading (Kid's Voice) 4. Story Reading (No Music & Sound Effects) Duck and his friends are at it again. But this time they’re pooling their consi

Beep! Beep! Sheep in a jeep on a hill that’s steep. Sheep in a Jeep is well loved by the preschool and early-reader sets for its slapstick story of five sheep (in a jeep) and silly sound effects—espec

Beep! Beep! Sheep in a jeep on a hill that’s steep. Sheep in a Jeep is well loved by the preschool and early-reader sets for its slapstick story of five sheep (in a jeep) and silly sound effects—espec

It’s Little Frog’s birthday, and Mama Frog gets a big surprise when the guests show up for his party－all he animals are the wrong color! Little Frog tells her she’s not looking long enough, and he’s r

Critically analyzes the American capitalistic system using Marx's view of competitive capitalism as a model

This is a practical guide to P-splines, a simple, flexible and powerful tool for smoothing. P-splines combine regression on B-splines with simple, discrete, roughness penalties. They were introduced by the authors in 1996 and have been used in many diverse applications. The regression basis makes it straightforward to handle non-normal data, like in generalized linear models. The authors demonstrate optimal smoothing, using mixed model technology and Bayesian estimation, in addition to classical tools like cross-validation and AIC, covering theory and applications with code in R. Going far beyond simple smoothing, they also show how to use P-splines for regression on signals, varying-coefficient models, quantile and expectile smoothing, and composite links for grouped data. Penalties are the crucial elements of P-splines; with proper modifications they can handle periodic and circular data as well as shape constraints. Combining penalties with tensor products of B-splines extends these

This volume deals with first- and second-order complex equations of hyperbolic and mixed types. The authors investigate in detail general boundary value problems for linear and quasilinear complex equ

The material covered by this book consists of a collection of regression models beyond linear regression. The linear regression model is presented in the first chapter in order to refresh the reader’s

This book provides a handy, unified introduction to the theory of compact extended formulations of exponential-size integer linear programming (ILP) models. Compact extended formulations are equally p

Quantitative Methods in Archaeology Using R is the first hands-on guide to using the R statistical computing system written specifically for archaeologists. It shows how to use the system to analyze many types of archaeological data. Part I includes tutorials on R, with applications to real archaeological data showing how to compute descriptive statistics, create tables, and produce a wide variety of charts and graphs. Part II addresses the major multivariate approaches used by archaeologists, including multiple regression (and the generalized linear model); multiple analysis of variance and discriminant analysis; principal components analysis; correspondence analysis; distances and scaling; and cluster analysis. Part III covers specialized topics in archaeology, including intra-site spatial analysis, seriation, and assemblage diversity.

Quantitative Methods in Archaeology Using R is the first hands-on guide to using the R statistical computing system written specifically for archaeologists. It shows how to use the system to analyze many types of archaeological data. Part I includes tutorials on R, with applications to real archaeological data showing how to compute descriptive statistics, create tables, and produce a wide variety of charts and graphs. Part II addresses the major multivariate approaches used by archaeologists, including multiple regression (and the generalized linear model); multiple analysis of variance and discriminant analysis; principal components analysis; correspondence analysis; distances and scaling; and cluster analysis. Part III covers specialized topics in archaeology, including intra-site spatial analysis, seriation, and assemblage diversity.

Using the open source R language, you can build powerful statistical models to answer many of your most challenging questions. R has traditionally been difficult for non-statisticians to learn, and mo

This book presents a greatly enlarged statistical framework compared to generalized linear models (GLMs) with which to approach regression modelling. Comprising of about half-a-dozen major classes of

The purpose of this book is to define a broad spectrum of statistical linear models that is useful in the analysis of data. Considered a "classic" for years, the material in this book is now

This book presents a greatly enlarged statistical framework compared to generalized linear models (GLMs) with which to approach regression modelling. Comprising of about half-a-dozen major classes of

Focusing on robust rank-based nonparametric methods, this book covers rank-based fitting and testing for models ranging from simple location models to general linear models for uncorrelated and correl

Suitable for researchers and graduate students in the social sciences, this book shows how to apply spatial models using R to a wide range of data from political science and related areas. It also cov

This graduate-level guide introduces concepts, assumptions, and practical implementation procedures in hierarchical linear modeling (also known as multilevel modeling or linear mixed modeling). The fi

Multivariate General Linear Models is an integrated introduction to multivariate multiple regression analysis (MMR) and multivariate analysis of variance (MANOVA). Beginning with an overview of the un

This volume contains articles focusing on the use of linear algebra as an indispensable tool in researching Markov chains and queueing models. Markov chains and queueing models play an increasingly im

In teaching linear statistical models to first-year graduate students or to final-year undergraduate students there is no way to proceed smoothly without matrices and related concepts of linear algebr

This new edition of Stochastic Linear Programming: Models, Theory and Computation has been brought completely up to date, either dealing with or at least referring to new material on models and method

Linear Algebra: An Introduction With Mathematica uses a matrix-based presentation and covers the standard topics any mathematician will need to understand linear algebra while using Mathematica. Devel

A Primer on Linear Models presents a unified, thorough, and rigorous development of the theory behind the statistical methodology of regression and analysis of variance (ANOVA). It seamlessly incorpor

This is the only book actuaries need to understand generalized linear models (GLMs) for insurance applications. GLMs are used in the insurance industry to support critical decisions. Until now, no text has introduced GLMs in this context or addressed the problems specific to insurance data. Using insurance data sets, this practical, rigorous book treats GLMs, covers all standard exponential family distributions, extends the methodology to correlated data structures, and discusses recent developments which go beyond the GLM. The issues in the book are specific to insurance data, such as model selection in the presence of large data sets and the handling of varying exposure times. Exercises and data-based practicals help readers to consolidate their skills, with solutions and data sets given on the companion website. Although the book is package-independent, SAS code and output examples feature in an appendix and on the website. In addition, R code and output for all the examples are pro

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

Revised and updated with the latest results, this Third Edition explores the theory and applications of linear models. The authors present a unified theory of inference from linear models and its gene

With a focus on analyzing and modeling linear dynamic systems using statistical methods, Time Series Analysis formulates various linear models, discusses their theoretical characteristics, and explore

This book is about the coordinate-free, or geometric, approach to the theory of linear models; more precisely, Model I ANOVA and linear regression models with non-random predictors in a finite-dimensional setting. This approach is more insightful, more elegant, more direct, and simpler than the more common matrix approach to linear regression, analysis of variance, and analysis of covariance models in statistics. The book discusses the intuition behind and optimal properties of various methods of estimating and testing hypotheses about unknown parameters in the models. Topics covered range from linear algebra, such as inner product spaces, orthogonal projections, book orthogonal spaces, Tjur experimental designs, basic distribution theory, the geometric version of the Gauss-Markov theorem, optimal and non-optimal properties of Gauss-Markov, Bayes, and shrinkage estimators under assumption of normality, the optimal properties of F-test, and the analysis of covariance and missing observa

Kutner, Nachtsheim, Neter, Wasserman, Applied Linear Regression Models, 4/e (ALRM4e) is the long established leading authoritative text and reference on regression (previously Neter was lead author.)

Linear Algebra: An Introduction Using MAPLE is a text for a first undergraduate course in linear algebra. All students majoring in mathematics, computer science, engineering, physics, chemistry, econo

This book describes the Bayesian approach to statistics at a level suitable for final year undergraduate and Masters students. It is unusual in presenting Bayesian statistics with a practical flavor and an emphasis on mainstream statistics, showing how to infer scientific, medical, and social conclusions from numerical data. The authors draw on many years of experience with practical and research programs and describe many statistical methods, not readily available elsewhere. A first chapter on Fisherian methods, together with a strong overall emphasis on likelihood, makes the text suitable for mainstream statistics courses whose instructors wish to follow mixed or comparative philosophies. The other chapters contain important sections relating to many areas of statistics such as the linear model, categorical data analysis, time series and forecasting, mixture models, survival analysis, Bayesian smoothing, and non-linear random effects models. The text includes a large number of practi

This book describes the Bayesian approach to statistics at a level suitable for final year undergraduate and Masters students. It is unusual in presenting Bayesian statistics with a practical flavor and an emphasis on mainstream statistics, showing how to infer scientific, medical, and social conclusions from numerical data. The authors draw on many years of experience with practical and research programs and describe many statistical methods, not readily available elsewhere. A first chapter on Fisherian methods, together with a strong overall emphasis on likelihood, makes the text suitable for mainstream statistics courses whose instructors wish to follow mixed or comparative philosophies. The other chapters contain important sections relating to many areas of statistics such as the linear model, categorical data analysis, time series and forecasting, mixture models, survival analysis, Bayesian smoothing, and non-linear random effects models. The text includes a large number of practi

The success of the first edition of Generalized Linear Models led to the updated Second Edition, which continues to provide a definitive unified, treatment of methods for the analysis of diverse types

From the creators of the 10-million-copy bestselling Paint by Sticker(R) Kids sticker-activity series, the next book in the brand extension developed especially for kids ages 3 and up: Construction Site! My First Paint by Sticker delivers the same screen-free, mess-free fun that makes the original series so irresistable. The fourth book in the series features construction site vehicles! From diggers to backhoes to cement trucks and more, kids will adore stickering these colorful machines. The Paint by Sticker Kids(R) series (for ages 5 and up) has sold more than 10 million copies to date. In My First Paint by Sticker, readers ages 3 and up can confidently paint by sticker, too! At a smaller trim size (8 x 8 inches, versus the original kids brand at 9 x 9), this brand extension features larger stickers for smaller hands--perfect for kids practicing their fine motor skills and learning to recognize their numbers. In the older kids series, the number of stickers per image ranges from 60-1