Linear Mixed-Effects Models Using R

Most texts on nonparametric techniques concentrate on location and linear-linear (correlation) tests, with less emphasis on dispersion effects and linear-quadratic tests. Tests for higher moment effec

The theory of linear poroelasticity describes the interaction between mechanical effects and adding or removing fluid from rock. It is critical to the study of such geological phenomena as earthquakes

Looking for a practical guide to using mixed methodologies? Authors Abbas Tashakkori and Charles Teddlie explore the most resourceful way to combine qualitative and quantitative methodologies. Beginn

This book describes an array of power tools for data analysis that are based on nonparametric regression and smoothing techniques. These methods relax the linear assumption of many standard models and

Gain hands-on experience creating, manipulating, and optimizing motion graphics for film, video, the web, and mobile devices. Learn how to animate text and images, customize a wide range of effects, track and sync content, rotoscope, manipulate timing, correct color, and remove unwanted objects. Customize cameras and lighting to create compelling 3D content. Design Motion Graphics templates for editing in Adobe Premiere Pro. Deform and animate objects and video using robust Puppet tools. The fastest, easiest, most comprehensive way to learn Adobe After Effects Classroom in a Book(R), the best-selling series of hands-on software training workbooks, offers what no other book or training program does--an official training series from Adobe, developed with the support of Adobe product experts. Adobe After Effects Classroom in a Book contains 15 lessons that cover the basics and beyond, providing countless tips and techniques to help you become more productive with the program. You can foll

Exploring the phenomenon of 'mixed categories', this book is the first in-depth study of the way in which languages can use a noun, as opposed to an adjective, to modify another noun. It investigates noun-adjective hybrids - adjectives and adjective-like attributive forms which have been derived from nouns and systematically retain certain nominal properties. These rarely-discussed types of mixed category raise a number of important theoretical questions about the nature of lexemic identity, the inflection-derivation divide, and more generally, the relationship between the structure of words and their phrasal syntax. The book proposes a new formal framework that models cross-linguistic and cross-constructional variation in noun modification constructions. The framework it offers enables readers to explicitly map word structure to syntactic structure, providing new insights into, and impacting upon, all current theoretical models of grammar.

Chunyan Li is a course instructor with many years of experience in teaching about time series analysis. His book is essential for students and researchers in oceanography and other subjects in the Earth sciences, looking for a complete coverage of the theory and practice of time series data analysis using MATLAB. This textbook covers the topic's core theory in depth, and provides numerous instructional examples, many drawn directly from the author's own teaching experience, using data files, examples, and exercises. The book explores many concepts, including time; distance on Earth; wind, current, and wave data formats; finding a subset of ship-based data along planned or random transects; error propagation; Taylor series expansion for error estimates; the least squares method; base functions and linear independence of base functions; tidal harmonic analysis; Fourier series and the generalized Fourier transform; filtering techniques: sampling theorems: finite sampling effects; wavelet

Designed as a textbook for a one or two-term introduction to mathematical statistics for students training to become data scientists, Foundations of Statistics for Data Scientists: With R and Python is an in-depth presentation of the topics in statistical science with which any data scientist should be familiar, including probability distributions, descriptive and inferential statistical methods, and linear modelling. The book assumes knowledge of basic calculus, so the presentation can focus on 'why it works' as well as 'how to do it.' Compared to traditional "mathematical statistics" textbooks, however, the book has less emphasis on probability theory and more emphasis on using software to implement statistical methods and to conduct simulations to illustrate key concepts. All statistical analyses in the book use R software, with an appendix showing the same analyses with Python.The book also introduces modern topics that do not normally appear in mathematical statistics texts but ar

Applied Biomedical Engineering Using Artificial Intelligence and Cognitive Models focuses on the relationship between three different multidisciplinary branches of engineering: Biomedical Engineering, Cognitive Science and Computer Science through Artificial Intelligence models. These models will be used to study how the nervous system and musculoskeletal system obey movement orders from the brain, as well as the mental processes of the information during cognition when injuries and neurologic diseases are present in the human body. The interaction between these three areas are studied in this book with the objective of obtaining AI models on injuries and neurologic diseases of the human body, studying diseases of the brain, spine and the nerves that connect them with the musculoskeletal system.There are more than 600 diseases of the nervous system, including brain tumors, epilepsy, Parkinson's disease, stroke, and many others. These diseases affect the human cognitive system that send

An R Companion for the Third Edition of The Fundamentals of Political Science Research offers students a chance to delve into the world of R using real political data sets and statistical analysis techniques directly from Paul M. Kellstedt and Guy D. Whitten's best-selling textbook. Built in parallel with the main text, this workbook teaches students to apply the techniques they learn in each chapter by reproducing the analyses and results from each lesson using R. Students will also learn to create all of the tables and figures found in the textbook, leading to an even greater mastery of the core material. This accessible, informative, and engaging companion walks through the use of R step-by-step, using command lines and screenshots to demonstrate proper use of the software. With the help of these guides, students will become comfortable creating, editing, and using data sets in R to produce original statistical analyses for evaluating causal claims. End-of-chapter exercises encourag

Join a wild and wacky Easter egg hunt in this egg-citing LEGO(R) Iconic activity book. It includes everything you need to build three exclusive LEGO(R) models!Join a wild and wacky Easter egg hunt in

This Element discusses how shiny, an R package, can help instructors teach quantitative methods more effectively by way of interactive web apps. The interactivity increases instructors' effectiveness by making students more active participants in the learning process, allowing them to engage with otherwise complex material in an accessible, dynamic way. The Element offers four detailed apps that cover two fundamental linear regression topics: estimation methods (least squares, maximum likelihood) and the classic linear regression assumptions. It includes a summary of what the apps can be used to demonstrate, detailed descriptions of the apps' full capabilities, vignettes from actual class use, and example activities. Two other apps pertain to a more advanced topic (LASSO), with similar supporting material. For instructors interested in modifying the apps, the Element also documents the main apps' general code structure, highlights some of the more likely modifications, and goes through

China-Africa economic tie has experienced lasting rapid growth since the 2000s, attracting lots of discussion on its nature and effects. A key question is whether Chinese engagements provide an alternative paradigm to existing mainstream models, like Washington Consensus, for developing countries. However, theories on state-market dichotomy can hardly explain the strong momentum of bilateral cooperation. By examining a broad range of practices with solid field research, including trade, infrastructure, agriculture, manufacturing, industrial zones, labor and socio-environmental preservation, this book proposes a new angle of non-linear circular causality to understand Chinese approaches to work with Africa. Guided by the pursuit for sustainable growth rather than by specific models, Chinese actors are able to experiment diverse methods to foster structural transformation in Africa. In particular, the author carefully records mutual influences between Chinese and African stakeholders at

In his latest book, Joachim (Joe) Klang presents the reader with a fascinating choice of exclusively designed LEGO (R) models, featuring cool, classic objects that everyone will recognise. With illu

Biostatistics with R provides a straightforward introduction on how to analyse data from the wide field of biological research, including nature protection and global change monitoring. The book is centred around traditional statistical approaches, focusing on those prevailing in research publications. The authors cover t-tests, ANOVA and regression models, but also the advanced methods of generalised linear models and classification and regression trees. Chapters usually start with several useful case examples, describing the structure of typical datasets and proposing research-related questions. All chapters are supplemented by example datasets, step-by-step R code demonstrating analytical procedures and interpretation of results. The authors also provide examples of how to appropriately describe statistical procedures and results of analyses in research papers. This accessible textbook will serve a broad audience, from students, researchers or professionals looking to improve their

Biostatistics with R provides a straightforward introduction on how to analyse data from the wide field of biological research, including nature protection and global change monitoring. The book is centred around traditional statistical approaches, focusing on those prevailing in research publications. The authors cover t-tests, ANOVA and regression models, but also the advanced methods of generalised linear models and classification and regression trees. Chapters usually start with several useful case examples, describing the structure of typical datasets and proposing research-related questions. All chapters are supplemented by example datasets, step-by-step R code demonstrating analytical procedures and interpretation of results. The authors also provide examples of how to appropriately describe statistical procedures and results of analyses in research papers. This accessible textbook will serve a broad audience, from students, researchers or professionals looking to improve their

Introduction to Time Series Modeling: with Applications in R, Second Edition covers numerous stationary and nonstationary time series models and tools for estimating and utilizing them. The goal

Introduction to Time Series Modeling: with Applications in R, Second Edition covers numerous stationary and nonstationary time series models and tools for estimating and utilizing them. The goal

Discover the past like never before - in LEGO (R) bricks! Discover the history of the world and get inspired to build your own epic LEGO (R) models! The book also comes with bricks to make four exclus

Drawing on examples from across the social and behavioral sciences, Statistics with R: Solving Problems Using Real-World Data introduces foundational statistics concepts with beginner-friendly R progr

In this new book, Porsche 911: Legends Made of LEGO (R) , by Joachim (Joe) Klang, LEGO (R) enthusiasts can bring sports cars from the legendary Porsche 911 series to life in their own home using their

Building on the Cambridge Element Agent Based Models of Social Life: Fundamentals (Cambridge, 2020), we move on to the next level. We do this by building agent based models of polarization and ethnocentrism. In the process, we develop: stochastic models, which add a crucial element of uncertainty to human interaction; models of human interactions structured by social networks; and 'evolutionary' models in which agents using more effective decision rules are more likely to survive and prosper than others. The aim is to leave readers with an effective toolkit for building, running and analyzing agent based modes of social interaction.

Exploring the phenomenon of 'mixed categories', this book is the first in-depth study of the way in which languages can use a noun, as opposed to an adjective, to modify another noun. It investigates noun-adjective hybrids - adjectives and adjective-like attributive forms which have been derived from nouns and systematically retain certain nominal properties. These rarely-discussed types of mixed category raise a number of important theoretical questions about the nature of lexemic identity, the inflection-derivation divide, and more generally, the relationship between the structure of words and their phrasal syntax. The book proposes a new formal framework that models cross-linguistic and cross-constructional variation in noun modification constructions. The framework it offers enables readers to explicitly map word structure to syntactic structure, providing new insights into, and impacting upon, all current theoretical models of grammar.

Linear and Non-Linear Deformations of Elastic Solids aims to compile the advances in the field of linear and non-linear elasticity through discussion crack, contact, scattering and wave propagation in

An introduction to the use of probability models for analyzing risk and economic decisions, using spreadsheets to represent and simulate uncertainty. This textbook offers an introduction to the use

Introduction to Statistics Using R is organized into 13 major chapters.Each chapter is broken down into many digestible subsections in order to explore the objectives of the book. There are many real-

This book presents an eclectic selection of a hundred graphic design projects that are drawn from a wide variety of areas and incorporate three-dimensional effects. Through using 3D tools, each of the

Gain insights into image-processing methodologies and algorithms, using machine learning and neural networks in Python. This book begins with the environment setup, understanding basic image-processing terminology, and exploring Python concepts that will be useful for implementing the algorithms discussed in the book. You will then cover all the core image processing algorithms in detail before moving onto the biggest computer vision library: OpenCV. You’ll see the OpenCV algorithms and how to use them for image processing. The next section looks at advanced machine learning and deep learning methods for image processing and classification. You’ll work with concepts such as pulse coupled neural networks, AdaBoost, XG boost, and convolutional neural networks for image-specific applications. Later you’ll explore how models are made in real time and then deployed using various DevOps tools. All the concepts in Practical Machine Learning and Image Processing are explained using r

This book introduces two-dimensional supersymmetric field theories with emphasis on both linear and non-linear sigma models. Complex differential geometry, in connection with supersymmetry, has played

Examine the latest technological advancements in building a scalable machine-learning model with big data using R. This second edition shows you how to work with a machine-learning algorithm and use i

Using the popular Heat Transfer Module from COMSOL, this text is designed to provide models for investigating and analyzing heat transfer applications such as conduction, convection, and radiation, et

This textbook presents an introduction to multiple linear regression, providing real-world data sets and practice problems. A practical working knowledge of applied statistical practice is developed t

Economic Role of Transport Infrastructure: Theory and Models helps evaluate the economic effects of transport infrastructure investments within a cost-benefit framework for maximum economic impact. Th

This book presents the R software environment as a key tool for oceanographic computations and provides a rationale for using R over the more widely-used tools of the field such as MATLAB. Kelley prov

Using IBM(r) SPSS(r) Statistics, 3rd Edition by James Aldrich gives readers a very accessible and comprehensive guide to walking through SPSS(r), providing them with step-by-step knowledge for effecti

Solitons emerge in various non-linear systems as stable localized configurations, behaving in many ways like particles, from non-linear optics and condensed matter to nuclear physics, cosmology and supersymmetric theories. This book provides an introduction to integrable and non-integrable scalar field models with topological and non-topological soliton solutions. Focusing on both topological and non-topological solitons, it brings together debates around solitary waves and construction of soliton solutions in various models and provides a discussion of solitons using simple model examples. These include the Kortenweg-de-Vries system, sine-Gordon model, kinks and oscillons, and skyrmions and hopfions. The classical field theory of scalar field in various spatial dimensions is used throughout the book in presentation of related concepts, both at the technical and conceptual level. Providing a comprehensive introduction to the description and construction of solitons, this book is ideal

Panel Data Econometrics with R provides a tutorial for using R in the field of panel data econometrics. Illustrated throughout with examples in econometrics, political science, agriculture and epidemi

This book is a comprehensive guide to qualitative comparative analysis (QCA) using R. Using Boolean algebra to implement principles of comparison used by scholars engaged in the qualitative study of

Econometrics refers to a particular type of statistical models that are used to test and forecast future economic trends. The models used in this subject are logit, hazard, tobit, linear regression, e