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"Marilyn Campbell is at the top of her storytelling craft with this enticing time-travel romance. Be prepared for an all-night read . . ." ~Ellen G. Wulf, Verified Reviewer A Young 1950s War-Widow Time Travels to 2016 to Save a Stranger's Life At the Risk of Her Own in Marilyn Campbell's Paranormal Time-Travel Romance, JUST IN TIME -- 1950s to 2016 -- When Beverly Newcastle, a young 1950s war-widow, encounters a gypsy fortune teller with a magic potion, she's tossed 5 decades into the future and lands in the arms of Josh Colby, a half-Mohawk, Harley-riding bouncer. Desperate to clear his imprisoned grandfather of a murder he did not commit, Josh learns that Beverly holds the key. To turn that key, Beverly must travel back to her own time. But by the time he and Beverly figure out how to send her back, Beverly also holds the key to his heart. Publisher's Note: Readers who enjoy romance, sex and mystery as well as fans of Callie Langridge, Bethany Claire, Gillian Doyle and Barbara Longley will certainly enjoy Marilyn Campbell's fun romp through time. "If you're a time-travel fan, this is the book for you. . . . you almost believe it could really happen." ~Mona R. Anderson THE LOVERS IN TIME SERIES, in order Out of Time Just in Time Some Time Away It's About Time THE INNERWORLD AFFAIRS SERIES, in order Romulus Falcon Gallant Gabriel Logan Roman Blaze MARILYN CAMPBELL has been published in the genres of suspense, futuristic, time-travel, paranormal, erotic and lighthearted contemporary romances, non-fiction metaphysical works and has had a screenplay produced. A true thrill-junkie, she has jumped out of an airplane, raced around the Indy 500 track, driven solo throughout the United States and believes a labyrinth walk under the full moon can have magical results. Unfortunately, Marilyn has not yet figured out how to time-travel...except in her stories. She currently resides in western Massachusetts.
The Athens Conference on Applied Probability and Time Series in 1995 brought together researchers from across the world. The published papers appear in two volumes. Volume I includes papers on applied probability in Honor of J.M. Gani. The topics include probability and probabilistic methods in recursive algorithms and stochastic models, Markov and other stochastic models such as Markov chains, branching processes and semi-Markov systems, biomathematical and genetic models, epidemilogical models including S-I-R (Susceptible-Infective-Removal), household and AIDS epidemics, financial models for option pricing and optimization problems, random walks, queues and their waiting times, and spatial models for earthquakes and inference on spatial models.
Advances in Geosciences is the result of a concerted effort in bringing the latest results and planning activities related to earth and space science in Asia and the international arena. The volume editors are all leading scientists in their research fields covering six sections: Hydrological Science (HS), Planetary Science (PS), Solar Terrestrial (ST), Solid Earth (SE), Ocean Science (OS) and Atmospheric Science (AS). The main purpose is to highlight the scientific issues essential to the study of earthquakes, tsunamis, atmospheric dust storms, climate change, drought, flood, typhoons, monsoons, space weather, and planetary exploration.
Time Series Analysis in Seismology: Practical Applications provides technical assistance and coverage of available methods to professionals working in the field of seismology. Beginning with a thorough review of open problems in geophysics, including tectonic plate dynamics, localization of solitons, and forecasting, the book goes on to describe the various types of time series or punctual processes obtained from those systems. Additionally, the book describes a variety of methods and techniques relating to seismology and includes a discussion of future developments and improvements. Time Series Analysis in Seismology offers a concise presentation of the most recent advances in the analysis of geophysical data, particularly with regard to seismology, making it a valuable tool for researchers and students working in seismology and geophysics. Presents the necessary tools for time series analysis as it relates to seismology in a compact and consistent manner Includes a discussion of technical resources that can be applied to time series data analysis across multiple disciplines Describes the methods and techniques available for solving problems related to the analysis of complex data sets Provides exercises at the end of each chapter to enhance comprehension
This book gathers outstanding research papers presented at the 5th International Joint Conference on Advances in Computational Intelligence (IJCACI 2021), held online during October 23–24, 2021. IJCACI 2021 is jointly organized by Jahangirnagar University (JU), Bangladesh, and South Asian University (SAU), India. The book presents the novel contributions in areas of computational intelligence and it serves as a reference material for advance research. The topics covered are collective intelligence, soft computing, optimization, cloud computing, machine learning, intelligent software, robotics, data science, data security, big data analytics, and signal and natural language processing.
This proceedings volume contains extended abstracts of talks presented at the 18th Symposium on Operations Research held at the University of Cologne, September 1-3, 1993. The Symposia on Operations Research are the annual meetings of the Gesellschaft fiir Mathematik, Okonometrie und Operations Research (GMOOR), a scientific society providing a link between research and applications in the areas of applied mathematics, economics and operations research. The broad range of interests and scientific activities covered by GMOOR and its members was demonstrated by about 250 talks presented at the 18th Symposium. As in l'ecent years, emphasis was placed on optimization and stochastics, this year with a special focus on combinatorial optimization and discrete mathematics. We appreciate that with sections on parallel and distributed computing and on scientific computing also new fields could be integrated into the scope of the GMOOR. This book contains extended abstracts of most of the papers presented at the con ference. Long versions and full papers of the talks are expected to appear elsewhere in refereed periodicals. The contributions were divided into sixteen sections: (1) Theory of Optimization, (2) Computational Methods of Optimization, (3) Combinatorial Optimization and Dis crete Mathematics, (4) Scientific Computing, (5) Decision Theory, (6) Mathematical Economics and Game Theory, (7) Banking, Finance and Insurance, (8) Econometrics, (9) Macroeconomics and Economic Theory, (10) Stochastics, (11) Production and Lo gistics, (12) System and Control Theory, (13) Routing and Scheduling, (14) Knowledge Based Systems, (15) Information Systems and (16) Parallel and Distributed Compu ting.
Create and improve high-quality automated forecasts for time series data that have strong seasonal effects, holidays, and additional regressors using Python Key Features Learn how to use the open-source forecasting tool Facebook Prophet to improve your forecasts Build a forecast and run diagnostics to understand forecast quality Fine-tune models to achieve high performance, and report that performance with concrete statistics Book Description Prophet enables Python and R developers to build scalable time series forecasts. This book will help you to implement Prophet's cutting-edge forecasting techniques to model future data with higher accuracy and with very few lines of code. You will begin by exploring the evolution of time series forecasting, from the basic early models to the advanced models of the present day. The book will demonstrate how to install and set up Prophet on your machine and build your first model with only a few lines of code. You'll then cover advanced features such as visualizing your forecasts, adding holidays, seasonality, and trend changepoints, handling outliers, and more, along with understanding why and how to modify each of the default parameters. Later chapters will show you how to optimize more complicated models with hyperparameter tuning and by adding additional regressors to the model. Finally, you'll learn how to run diagnostics to evaluate the performance of your models and see some useful features when running Prophet in production environments. By the end of this Prophet book, you will be able to take a raw time series dataset and build advanced and accurate forecast models with concise, understandable, and repeatable code. What you will learn Gain an understanding of time series forecasting, including its history, development, and uses Understand how to install Prophet and its dependencies Build practical forecasting models from real datasets using Python Understand the Fourier series and learn how it models seasonality Decide when to use additive and when to use multiplicative seasonality Discover how to identify and deal with outliers in time series data Run diagnostics to evaluate and compare the performance of your models Who this book is for This book is for data scientists, data analysts, machine learning engineers, software engineers, project managers, and business managers who want to build time series forecasts in Python. Working knowledge of Python and a basic understanding of forecasting principles and practices will be useful to apply the concepts covered in this book more easily.
Provides a simple exposition of the basic time series material, and insights into underlying technical aspects and methods of proof Long memory time series are characterized by a strong dependence between distant events. This book introduces readers to the theory and foundations of univariate time series analysis with a focus on long memory and fractional integration, which are embedded into the general framework. It presents the general theory of time series, including some issues that are not treated in other books on time series, such as ergodicity, persistence versus memory, asymptotic properties of the periodogram, and Whittle estimation. Further chapters address the general functional central limit theory, parametric and semiparametric estimation of the long memory parameter, and locally optimal tests. Intuitive and easy to read, Time Series Analysis with Long Memory in View offers chapters that cover: Stationary Processes; Moving Averages and Linear Processes; Frequency Domain Analysis; Differencing and Integration; Fractionally Integrated Processes; Sample Means; Parametric Estimators; Semiparametric Estimators; and Testing. It also discusses further topics. This book: Offers beginning-of-chapter examples as well as end-of-chapter technical arguments and proofs Contains many new results on long memory processes which have not appeared in previous and existing textbooks Takes a basic mathematics (Calculus) approach to the topic of time series analysis with long memory Contains 25 illustrative figures as well as lists of notations and acronyms Time Series Analysis with Long Memory in View is an ideal text for first year PhD students, researchers, and practitioners in statistics, econometrics, and any application area that uses time series over a long period. It would also benefit researchers, undergraduates, and practitioners in those areas who require a rigorous introduction to time series analysis.
This book represents an integration of theory, methods, and examples using the S-PLUS statistical modeling language and the S+FinMetrics module to facilitate the practice of financial econometrics. It is the first book to show the power of S-PLUS for the analysis of time series data. It is written for researchers and practitioners in the finance industry, academic researchers in economics and finance, and advanced MBA and graduate students in economics and finance. Readers are assumed to have a basic knowledge of S-PLUS and a solid grounding in basic statistics and time series concepts. This edition covers S+FinMetrics 2.0 and includes new chapters.
Discover the official resource for success on the 2025 CFA Level I exam. Get your copy of the CFA® Program Curriculum now. The 2025 CFA Program Curriculum Level I Box Set contains the content you need to perform well on the Level I CFA exam in 2025. Designed for candidates to use for exam preparation and professional reference purposes, this set includes the full official curriculum for Level I and is part of the larger CFA Candidate Body of Knowledge (CBOK). Covering all ten core topics found on the Level I exam, the 2025 CFA Program Curriculum Level I Box Set helps you: Develop critical knowledge and skills essential in the industry. Learn from financial thought leaders. Access market-relevant instruction. The set also features practice questions to assist with your mastery of key terms, concepts, and formulas. Volumes include: Volume 1: Quantitative Methods Volume 2: Economics Volume 3: Corporate Issuers Volume 4: Financial Statement Analysis Volume 5: Equity Investments Volume 6: Fixed Income Volume 7: Derivatives Volume 8: Alternative Investments Volume 9: Portfolio Management Volume 10:Ethical and Professional Standards Indispensable for anyone preparing for the 2025 Level I CFA exam, the 2025 CFA Program Curriculum Level I Box Set is a must-have resource for those seeking the foundational skills required to become a Chartered Financial Analyst®.