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Time Series for Data Science: Analysis and Forecasting (Chapman & Hall/CRC Texts in Statistical Science)
by Wayne A. Woodward Bivin Philip Sadler Stephen RobertsonData Science students and practitioners want to find a forecast that “works” and don’t want to be constrained to a single forecasting strategy, Time Series for Data Science: Analysis and Forecasting discusses techniques of ensemble modelling for combining information from several strategies. Covering time series regression models, exponential smoothing, Holt-Winters forecasting, and Neural Networks. It places a particular emphasis on classical ARMA and ARIMA models that is often lacking from other textbooks on the subject.This book is an accessible guide that doesn’t require a background in calculus to be engaging but does not shy away from deeper explanations of the techniques discussed.Features: Provides a thorough coverage and comparison of a wide array of time series models and methods: Exponential Smoothing, Holt Winters, ARMA and ARIMA, deep learning models including RNNs, LSTMs, GRUs, and ensemble models composed of combinations of these models. Introduces the factor table representation of ARMA and ARIMA models. This representation is not available in any other book at this level and is extremely useful in both practice and pedagogy. Uses real world examples that can be readily found via web links from sources such as the US Bureau of Statistics, Department of Transportation and the World Bank. There is an accompanying R package that is easy to use and requires little or no previous R experience. The package implements the wide variety of models and methods presented in the book and has tremendous pedagogical use.
Time-Series Forecasting
by Chris ChatfieldFrom the author of the bestselling "Analysis of Time Series," Time-Series Forecasting offers a comprehensive, up-to-date review of forecasting methods. It provides a summary of time-series modelling procedures, followed by a brief catalogue of many different time-series forecasting methods, ranging from ad-hoc methods through ARIMA and state-space
Time Series Forecasting Using Generative AI: Leveraging AI for Precision Forecasting
by Banglore Vijay Vishwas Sri Ram Macharla"Time Series Forecasting Using Generative AI introduces readers to Generative Artificial Intelligence (Gen AI) in time series analysis, offering an essential exploration of cutting-edge forecasting methodologies." The book covers a wide range of topics, starting with an overview of Generative AI, where readers gain insights into the history and fundamentals of Gen AI with a brief introduction to large language models. The subsequent chapter explains practical applications, guiding readers through the implementation of diverse neural network architectures for time series analysis such as Multi-Layer Perceptrons (MLP), WaveNet, Temporal Convolutional Network (TCN), Bidirectional Temporal Convolutional Network (BiTCN), Recurrent Neural Networks (RNN), Long Short-Term Memory (LSTM), Deep AutoRegressive(DeepAR), and Neural Basis Expansion Analysis(NBEATS) using modern tools. Building on this foundation, the book introduces the power of Transformer architecture, exploring its variants such as Vanilla Transformers, Inverted Transformer (iTransformer), DLinear, NLinear, and Patch Time Series Transformer (PatchTST). Finally, The book delves into foundation models such as Time-LLM, Chronos, TimeGPT, Moirai, and TimesFM enabling readers to implement sophisticated forecasting models tailored to their specific needs. This book empowers readers with the knowledge and skills needed to leverage Gen AI for accurate and efficient time series forecasting. By providing a detailed exploration of advanced forecasting models and methodologies, this book enables practitioners to make informed decisions and drive business growth through data-driven insights. ● Understand the core history and applications of Gen AI and its potential to revolutionize time series forecasting. ● Learn to implement different neural network architectures such as MLP, WaveNet, TCN, BiTCN, RNN, LSTM, DeepAR, and NBEATS for time series forecasting. ● Discover the potential of Transformer architecture and its variants, such as Vanilla Transformers, iTransformer, DLinear, NLinear, and PatchTST, for time series forecasting. <span sty
Time Series in Economics and Finance
by Tomas CipraThis book presents the principles and methods for the practical analysis and prediction of economic and financial time series. It covers decomposition methods, autocorrelation methods for univariate time series, volatility and duration modeling for financial time series, and multivariate time series methods, such as cointegration and recursive state space modeling. It also includes numerous practical examples to demonstrate the theory using real-world data, as well as exercises at the end of each chapter to aid understanding. This book serves as a reference text for researchers, students and practitioners interested in time series, and can also be used for university courses on econometrics or computational finance.
Time Series Indexing: Implement iSAX in Python to index time series with confidence
by Mihalis TsoukalosBuild and use the most popular time series index available today with Python to search and join time series at the subsequence level Purchase of the print or Kindle book includes a free PDF eBook.Key FeaturesLearn how to implement algorithms and techniques from research papersGet to grips with building time series indexes using iSAXLeverage iSAX to solve real-world time series problemsBook DescriptionTime series are everywhere, ranging from financial data and system metrics to weather stations and medical records. Being able to access, search, and compare time series data quickly is essential, and this comprehensive guide enables you to do just that by helping you explore SAX representation and the most effective time series index, iSAX. The book begins by teaching you about the implementation of SAX representation in Python as well as the iSAX index, along with the required theory sourced from academic research papers. The chapters are filled with figures and plots to help you follow the presented topics and understand key concepts easily. But what makes this book really great is that it contains the right amount of knowledge about time series indexing using the right amount of theory and practice so that you can work with time series and develop time series indexes successfully. Additionally, the presented code can be easily ported to any other modern programming language, such as Swift, Java, C, C++, Ruby, Kotlin, Go, Rust, and JavaScript. By the end of this book, you'll have learned how to harness the power of iSAX and SAX representation to efficiently index and analyze time series data and will be equipped to develop your own time series indexes and effectively work with time series data.What you will learnFind out how to develop your own Python packages and write simple Python testsUnderstand what a time series index is and why it is usefulGain a theoretical and practical understanding of operating and creating time series indexesDiscover how to use SAX representation and the iSAX indexFind out how to search and compare time seriesUtilize iSAX visualizations to aid in the interpretation of complex or large time seriesWho this book is forThis book is for practitioners, university students working with time series, researchers, and anyone looking to learn more about time series. Basic knowledge of UNIX, Linux, and Python and an understanding of basic programming concepts are needed to grasp the topics in this book. This book will also be handy for people who want to learn how to read research papers, learn from them, and implement their algorithms.
Time Series Modeling for Analysis and Control
by Kohei Ohtsu Hui Peng Genshiro KitagawaThis book presents multivariate time series methods for the analysis and optimal control of feedback systems. Although ships' autopilot systems are considered through the entire book, the methods set forth in this book can be applied to many other complicated, large, or noisy feedback control systems for which it is difficult to derive a model of the entire system based on theory in that subject area. The basic models used in this method are the multivariate autoregressive model with exogenous variables (ARX) model and the radial bases function net-type coefficients ARX model. The noise contribution analysis can then be performed through the estimated autoregressive (AR) model and various types of autopilot systems can be designed through the state-space representation of the models. The marine autopilot systems addressed in this book include optimal controllers for course-keeping motion, rolling reduction controllers with rudder motion, engine governor controllers, noise adaptive autopilots, route-tracking controllers by direct steering, and the reference course-setting approach. The methods presented here are exemplified with real data analysis and experiments on real ships. This book is highly recommended to readers who are interested in designing optimal or adaptive controllers not only of ships but also of any other complicated systems under noisy disturbance conditions.
Time Series Modeling of Neuroscience Data (Chapman & Hall/CRC Interdisciplinary Statistics)
by Tohru OzakiRecent advances in brain science measurement technology have given researchers access to very large-scale time series data such as EEG/MEG data (20 to 100 dimensional) and fMRI (140,000 dimensional) data. To analyze such massive data, efficient computational and statistical methods are required.Time Series Modeling of Neuroscience Data shows how to
Time Series Modelling with Unobserved Components
by Matteo M. PelagattiDespite the unobserved components model (UCM) having many advantages over more popular forecasting techniques based on regression analysis, exponential smoothing, and ARIMA, the UCM is not well known among practitioners outside the academic community. Time Series Modelling with Unobserved Components rectifies this deficiency by giving a practical o
Time Series Models: In econometrics, finance and other fields (Chapman And Hall/crc Monographs On Statistics And Applied Probability Ser. #65)
by D.R.Cox; D.V. Hinkley; O.E. Barndorff-NielsenThe analysis prediction and interpolation of economic and other time series has a long history and many applications. Major new developments are taking place, driven partly by the need to analyze financial data. The five papers in this book describe those new developments from various viewpoints and are intended to be an introduction accessible to readers from a range of backgrounds.The book arises out of the second Seminaire European de Statistique (SEMSTAT) held in Oxford in December 1994. This brought together young statisticians from across Europe, and a series of introductory lectures were given on topics at the forefront of current research activity. The lectures form the basis for the five papers contained in the book.The papers by Shephard and Johansen deal respectively with time series models for volatility, i.e. variance heterogeneity, and with cointegration. Clements and Hendry analyze the nature of prediction errors. A complementary review paper by Laird gives a biometrical view of the analysis of short time series. Finally Astrup and Nielsen give a mathematical introduction to the study of option pricing. Whilst the book draws its primary motivation from financial series and from multivariate econometric modelling, the applications are potentially much broader.
Time Series Models
by Philip Hans FransesThis book considers periodic time series models for seasonal data, characterized by parameters that differ across the seasons, and focuses on their usefulness for out-of-sample forecasting. Providing an up-to-date survey of the recent developments in periodic time series, the book presents a large number of empirical results. The first part of the book deals with model selection, diagnostic checking and forecasting of univariate periodic autoregressive models. Tests for periodic integration, are discussed, and an extensive discussion of the role of deterministic regressors in testing for periodic integration and in forecasting is provided. The second part discusses multivariate periodic autoregressive models. It provides an overview of periodic cointegration models, as these are the most relevant. This overview contains single-equation type tests and a full-system approach based on generalized method of moments. All methods are illustrated with extensive examples, andthe book will be of interest to advanced graduate students and researchers in econometrics, as well as practitioners looking for an understanding of how to approach seasonal data.
Time Series with Mixed Spectra
by Ta-Hsin LiTime series with mixed spectra are characterized by hidden periodic components buried in random noise. Despite strong interest in the statistical and signal processing communities, no book offers a comprehensive and up-to-date treatment of the subject. Filling this void, Time Series with Mixed Spectra focuses on the methods and theory for the stati
Time, Space, and Number in Physics and Psychology (Psychology Revivals)
by William R. UttalThe crux of the debate between proponents of behavioral psychology and cognitive psychology focuses on the issue of accessibility. Cognitivists believe that mental mechanisms and processes are accessible, and that their inner workings can be inferred from experimental observations of behavior. Behaviorists, on the contrary, believe that mental processes and mechanisms are inaccessible, and that nothing important about them can be inferred from even the most cleverly designed empirical studies. One argument that is repeatedly raised by cognitivists is that even though mental processes are not directly accessible, this should not be a barrier to unravelling the nature of the inner mental processes and mechanisms. Inference works for other sciences, such as physics, so why not psychology? If physics can work so successfully with their kind of inaccessibility to make enormous theoretical progress, then why not psychology? As with most previous psychological debates, there is no "killer argument" that can provide an unambiguous resolution. In its absence, author William Uttal explores the differing properties of physical and psychological time, space, and mathematics before coming to the conclusion that there are major discrepancies between the properties of the respective subject matters that make the analogy of comparable inaccessibilities a false one. This title was first published in 2008.
Time Travel: A Reality in Mesoscopic Physics
by P. Singha Deo Kanchan MeenaThis book is aimed at postgraduate and Ph.D. students specializing in condensed matter physics, quantum mechanics, and the theory of relativity. It explores fundamental problems in physics that can be addressed in the mesoscopic regime. Some of the key topics covered include: a) The state of a tunneling particle under a barrier b) A local description of the state of a quantum particle c) Reality of time travel leading to reconciliation of the classical and quantum laws The book also sets the stage for developing an alternative description of quantum mechanics and how scattering phase shift can be used to probe local density of states. It highlights essential differences from traditional statistical mechanics and discusses the potential applications and future technologies stemming from breakthroughs in basic science, which will be of interest to researchers.
Time-Varying Effect Modeling for the Behavioral, Social, and Health Sciences
by Stephanie T. Lanza Ashley N. Linden-CarmichaelThis book is the first to introduce applied behavioral, social, and health sciences researchers to a new analytic method, the time-varying effect model (TVEM). It details how TVEM may be used to advance research on developmental and dynamic processes by examining how associations between variables change across time. The book describes how TVEM is a direct and intuitive extension of standard linear regression; whereas standard linear regression coefficients are static estimates that do not change with time, TVEM coefficients are allowed to change as continuous functions of real time, including developmental age, historical time, time of day, days since an event, and so forth.The book introduces readers to new research questions that can be addressed by applying TVEM in their research. Readers gain the practical skills necessary for specifying a wide variety of time-varying effect models, including those with continuous, binary, and count outcomes. The book presents technical details of TVEM estimation and three novel empirical studies focused on developmental questions using TVEM to estimate age-varying effects, historical shifts in behavior and attitudes, and real-time changes across days relative to an event. The volume provides a walkthrough of the process for conducting each of these studies, presenting decisions that were made, and offering sufficient detail so that readers may embark on similar studies in their own research. The book concludes with comments about additional uses of TVEM in applied research as well as software considerations and future directions. Throughout the book, proper interpretation of the output provided by TVEM is emphasized.Time-Varying Effect Modeling for the Behavioral, Social, and Health Sciences is an essential resource for researchers, clinicians/practitioners as well as graduate students in developmental psychology, public health, statistics and methodology for the social, behavioral, developmental, and public health sciences.
Time-Varying Vector Fields and Their Flows
by Saber Jafarpour Andrew D. LewisThis short book provides a comprehensive and unified treatment of time-varying vector fields under a variety of regularity hypotheses, namely finitely differentiable, Lipschitz, smooth, holomorphic, and real analytic. The presentation of this material in the real analytic setting is new, as is the manner in which the various hypotheses are unified using functional analysis. Indeed, a major contribution of the book is the coherent development of locally convex topologies for the space of real analytic sections of a vector bundle, and the development of this in a manner that relates easily to classically known topologies in, for example, the finitely differentiable and smooth cases. The tools used in this development will be of use to researchers in the area of geometric functional analysis.
TIME A Year in Space: Inside Scott Kellys Historic Mission Is Travel to Mars Next?
by The Editors of TIME Jeffrey KlugerGo inside one of the most historic space missions ever in A YEAR IN SPACE, the new special edition from TIME, written by Apollo 13 author Jeffrey Kluger. A YEAR IN SPACE chronicles astronaut Scott Kelly's 340 days aboard the International Space Station (ISS) as part of NASA's exploration of the challenges of extended spaceflight. The most pressing question: Could humans endure the two-and-a-half-year trip to Mars and back?While science has some understanding of how space and zero gravity affect the human body, Scott and his twin brother, Mark, a retired astronaut who remained on Earth, have served as the perfect test and control subjects to explore these effects.This special edition, the companion piece to the TIME and PBS documentary series A Year in Space, provides exclusive coverage coupled with abundant photographs, many taken by Scott Kelly himself.Highlights include:An inside look at how Kelly conducted experiments aboard the ISS and how he spent his downtime.Landscape Mode: Breathtaking photographs taken by Scott Kelly from 250 miles above the Earth's surface.In interview with Samantha Cristoforetti, the first woman to spend 200 days in space, who spoke with TIME about her journey.
Timeless Quantum Mechanics and the Early Universe (Springer Theses)
by Leonardo ChataignierThe book is based on the author's PhD thesis, which deals with the concept of time in quantum gravity and its relevance for the physics of the early Universe. It presents a consistent and complete new relational formulation of quantum gravity (more specifically, of quantum mechanics models with diffeomorphism invariance), which is applied to potentially observable cosmological effects. The work provides answers to the following questions: How can the dynamics of quantum states of matter and geometry be defined in a diffeomorphism-invariant way? What is the relevant space of physical states and which operators act on it? How are the quantum states related to probabilities in the absence of a preferred time? The answers can provide a further part of the route to constructing a fundamental theory of quantum gravity. The book is well-suited to graduate students as well as professional researchers in the fields of general relativity and gravitation, cosmology, and quantum foundations.
The Times Machine!: Learn Multiplication and Division. . . Like, Yesterday!
by Danica McKellarLearn at home with help from The Wonder Years/Hallmark actress, math whiz, and New York Times bestselling author Danica McKellar using her acclaimed McKellar Math books! A revolutionary and FUN way for 2nd to 5th graders to memorize multiplication facts outside of the classroom is finally here!Join Mr. Mouse and Ms. Squirrel and experience an entirely new way of memorizing multiplication facts. Using colorful stories, silly rhymes, and more, Danica McKellar helps to break down the rules of multiplication and to translate many of the (often confusing!) multiplication and division methods taught in today's classrooms. This lively "times" travel adventure is a lifesaver for frustrated kids and parents everywhere and a great way to "zero out" worries about homework and tests. If Mr. Mouse can learn to have fun with math, anyone can!
Tinkerlab: A Hands-On Guide for Little Inventors
by Rachelle DoorleyEncourage tinkering, curiosity, and creative thinking in children of all ages with these 55 hands-on activities that explore art, science, and more The creator of the highly popular creativity site for kids, Tinkerlab.com, now delivers dozens of engaging, kid-tested, and easy-to-implement projects that will help parents and teachers bring out the natural tinkerer in every kid—even babies, toddlers, and preschoolers. The creative experiments shared in this book foster curiosity, promote creative and critical thinking, and encourage tinkering—mindsets that are important to children growing up in a world that values independent thinking. In addition to offering a host of activities that parents and teachers can put to use right away, this book also includes a buffet of recipes (magic potions, different kinds of play dough, silly putty, and homemade butter) and a detailed list of materials to include in the art pantry.
A Tiny Handbook of R (SpringerBriefs in Statistics)
by Mike AllerhandThis Brief provides a roadmap for the R language and programming environment with signposts to further resources and documentation.
The Tiny Traveler: A Book of Numbers
by Misti KenisonHow many gondolas float down the canal? Can you count the number of masks at Carnival? Toddlers will answer these questions and more in this new book from Misti Kenison in her Tiny Traveler series. Travel from Rome to Venice as you and your little one count your way through Italy’s most famous landmarks. From one leaning tower to seven fresh pizzas coming out of the oven, you’ll catch the travel bug while teaching children the basics of counting!The fourth book in Kenison’s Tiny Traveler board book series will exposure your child to another country and culture while teaching him or her the basic concept of counting and numbers. So sit back and explore the world with your little one from your very own living room. Traveling to foreign places has never been so fun, or educational, for young children before!A wonderful series for young toddlers (0 to 2 years), this book teaches the basic concept of numbers and counting. Can be used at home or in a childcare facility to teach basic concepts.
Tipler Physik: für Studierende der Naturwissenschaften und Technik
by Paul A. Tipler Gene MoscaTipler Physik dient bereits Generationen von Studierenden der Natur- und Ingenieurwissenschaften als Lern-, Lehr- und Nachschlagewerk. Angehende oder sich bereits im Studium befindliche Bachelorstudierende mit Physik, Ingenieurwissenschaften oder verwandter Gebiete, egal ob im Haupt- oder Nebenfach profitieren von ausführlichen und leicht nachvollziehbaren Erklärungen. Schritt für Schritt werden Beispiele vorgerechnet, zusätzlich oft auch mithilfe der Software MATLAB®. Zudem werden die physikalischen Inhalte mit wertvollen Tipps und Tricks vervollständigt. Alle Gebiete der Physik werden behandelt und zwar genau richtig – nicht zu viel um einen guten Einstieg zu ermöglichen und nicht zu wenig, um einen soliden Überblick zu erhalten. Damit ist Tipler Physik ein treuer Begleiter durch das Studium und auch danach. Gleichzeitig trägt das Buch neuen Entwicklungen Rechnung. Digitale Karteikarten, die in dieser Auflage neu hinzugekommen sind, ermöglichen das flexible Lernen und Vertiefen überall. Am Ende jedes Kapitels findet ein Ein- und Ausblick in die aktuelle Forschung statt.Wer im Studium, Schule oder Beruf sich mit physikalischen Fragestellungen befasst, dem sollte Tipler Physik in Bücherregal nicht fehlen: · didaktisch wertvoll aufbereitet und dargestellt· zahlreiche Beispiel- und Übungsaufgaben mit Schritt-für-Schritt Anleitungen bzw. Lösungen· digitale Karteikarten in Form der SN Flashcards· Einführung in MATLAB® anhand konkreter Aufgabenstellungen· bewährte Tipps und Tricks, um nicht in die Fehlerfalle zu geraten· wichtigste Gesetze und Formeln kurz zusammengefasst· übersichtliche und anschauliche Abbildungen· aktuelle Forschungsbeiträge, die in den Kontext zu ihrem Fachgebiet gestellt werden.
The Tipping Point: How Little Things Can Make a Big Difference
by Malcolm Gladwell'A wonderful page-turner about a fascinating idea that should affect the way every thinking person thinks about the world around him' Michael LewisIn this brilliant and original book, Malcolm Gladwell explains and analyses the 'tipping point', that magic moment when ideas, trends and social behaviour cross a threshold, tip and spread like wildfire. Taking a look behind the surface of many familiar occurrences in our everyday world, Gladwell explains the fascinating social dynamics that cause rapid change.'Hip and hopeful, THE TIPPING POINT is like the idea it describes: concise, elegant but packed with social power. A book for anyone who cares about how society works and how we can make it better' George Stephanopoulos
The Tipping Point: How Little Things Can Make a Big Difference
by Malcolm Gladwell'A wonderful page-turner about a fascinating idea that should affect the way every thinking person thinks about the world around him' Michael LewisIn this brilliant and original book, Malcolm Gladwell explains and analyses the 'tipping point', that magic moment when ideas, trends and social behaviour cross a threshold, tip and spread like wildfire. Taking a look behind the surface of many familiar occurrences in our everyday world, Gladwell explains the fascinating social dynamics that cause rapid change.'Hip and hopeful, THE TIPPING POINT is like the idea it describes: concise, elegant but packed with social power. A book for anyone who cares about how society works and how we can make it better' George Stephanopoulos
The Tipping Point: How Little Things Can Make a Big Difference
by Malcolm Gladwell'A wonderful page-turner about a fascinating idea that should affect the way every thinking person thinks about the world around him' Michael LewisIn this brilliant and original book, Malcolm Gladwell explains and analyses the 'tipping point', that magic moment when ideas, trends and social behaviour cross a threshold, tip and spread like wildfire. Taking a look behind the surface of many familiar occurrences in our everyday world, Gladwell explains the fascinating social dynamics that cause rapid change.'Hip and hopeful, THE TIPPING POINT is like the idea it describes: concise, elegant but packed with social power. A book for anyone who cares about how society works and how we can make it better' George Stephanopoulos