Some Aspects Of Time Series Frequency Estimation
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Some Aspects Of Time Series Frequency Estimation
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Author : Margaret S. Mackisack
language : en
Publisher:
Release Date : 1987
Some Aspects Of Time Series Frequency Estimation written by Margaret S. Mackisack and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1987 with Fourier analysis categories.
Time Series In The Frequency Domain
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Author : David R. Brillinger
language : en
Publisher:
Release Date : 1983
Time Series In The Frequency Domain written by David R. Brillinger and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1983 with Mathematics categories.
Hardbound. This volume of the Handbook is concerned particularly with the frequency side, or spectrum, approach to time series analysis. This approach involves essential use of sinusoids and bands of (angular) frequency, with Fourier transforms playing an important role. A principal activity is thinking of systems, their inputs, outputs, and behavior in sinusoidal terms. In many cases, the frequency side approach turns out to be simpler with respect to computational, mathematical, and statistical aspects. In the frequency approach, an assumption of stationarity is commonly made. However, the essential roles played by the techniques of complex demodulation and seasonal adjustment show that stationarity is far from being a necessary condition. Assumptions of Gaussianity and linearity are also commonly made and yet, as a variety of the papers illustrate, these assumptions are not necessary. This volume complements Handbook of Statistics 5: Time Series in the
Applied Time Series Analysis With R
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Author : Wayne A. Woodward
language : en
Publisher: CRC Press
Release Date : 2017-02-17
Applied Time Series Analysis With R written by Wayne A. Woodward and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-02-17 with Mathematics categories.
Virtually any random process developing chronologically can be viewed as a time series. In economics closing prices of stocks, the cost of money, the jobless rate, and retail sales are just a few examples of many. Developed from course notes and extensively classroom-tested, Applied Time Series Analysis with R, Second Edition includes examples across a variety of fields, develops theory, and provides an R-based software package to aid in addressing time series problems in a broad spectrum of fields. The material is organized in an optimal format for graduate students in statistics as well as in the natural and social sciences to learn to use and understand the tools of applied time series analysis. Features Gives readers the ability to actually solve significant real-world problems Addresses many types of nonstationary time series and cutting-edge methodologies Promotes understanding of the data and associated models rather than viewing it as the output of a "black box" Provides the R package tswge available on CRAN which contains functions and over 100 real and simulated data sets to accompany the book. Extensive help regarding the use of tswge functions is provided in appendices and on an associated website. Over 150 exercises and extensive support for instructors The second edition includes additional real-data examples, uses R-based code that helps students easily analyze data, generate realizations from models, and explore the associated characteristics. It also adds discussion of new advances in the analysis of long memory data and data with time-varying frequencies (TVF).
Fundamentals Of Clinical Data Science
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Author : Pieter Kubben
language : en
Publisher: Springer
Release Date : 2018-12-21
Fundamentals Of Clinical Data Science written by Pieter Kubben and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-12-21 with Medical categories.
This open access book comprehensively covers the fundamentals of clinical data science, focusing on data collection, modelling and clinical applications. Topics covered in the first section on data collection include: data sources, data at scale (big data), data stewardship (FAIR data) and related privacy concerns. Aspects of predictive modelling using techniques such as classification, regression or clustering, and prediction model validation will be covered in the second section. The third section covers aspects of (mobile) clinical decision support systems, operational excellence and value-based healthcare. Fundamentals of Clinical Data Science is an essential resource for healthcare professionals and IT consultants intending to develop and refine their skills in personalized medicine, using solutions based on large datasets from electronic health records or telemonitoring programmes. The book’s promise is “no math, no code”and will explain the topics in a style that is optimized for a healthcare audience.
Forecasting Principles And Practice
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Author : Rob J Hyndman
language : en
Publisher: OTexts
Release Date : 2018-05-08
Forecasting Principles And Practice written by Rob J Hyndman and has been published by OTexts this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-05-08 with Business & Economics categories.
Forecasting is required in many situations. Stocking an inventory may require forecasts of demand months in advance. Telecommunication routing requires traffic forecasts a few minutes ahead. Whatever the circumstances or time horizons involved, forecasting is an important aid in effective and efficient planning. This textbook provides a comprehensive introduction to forecasting methods and presents enough information about each method for readers to use them sensibly.
Recursive Estimation And Time Series Analysis
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Author : Peter C. Young
language : en
Publisher: Springer Science & Business Media
Release Date : 2011-08-04
Recursive Estimation And Time Series Analysis written by Peter C. Young and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-08-04 with Technology & Engineering categories.
This is a revised version of the 1984 book of the same name but considerably modified and enlarged to accommodate the developments in recursive estimation and time series analysis that have occurred over the last quarter century. Also over this time, the CAPTAIN Toolbox for recursive estimation and time series analysis has been developed at Lancaster, for use in the MatlabTM software environment (see Appendix G). Consequently, the present version of the book is able to exploit the many computational routines that are contained in this widely available Toolbox, as well as some of the other routines in MatlabTM and its other toolboxes. The book is an introductory one on the topic of recursive estimation and it demonstrates how this approach to estimation, in its various forms, can be an impressive aid to the modelling of stochastic, dynamic systems. It is intended for undergraduate or Masters students who wish to obtain a grounding in this subject; or for practitioners in industry who may have heard of topics dealt with in this book and, while they want to know more about them, may have been deterred by the rather esoteric nature of some books in this challenging area of study.
Introductory Time Series With R
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Author : Paul S.P. Cowpertwait
language : en
Publisher: Springer Science & Business Media
Release Date : 2009-05-28
Introductory Time Series With R written by Paul S.P. Cowpertwait and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-05-28 with Mathematics categories.
This book gives you a step-by-step introduction to analysing time series using the open source software R. Each time series model is motivated with practical applications, and is defined in mathematical notation. Once the model has been introduced it is used to generate synthetic data, using R code, and these generated data are then used to estimate its parameters. This sequence enhances understanding of both the time series model and the R function used to fit the model to data. Finally, the model is used to analyse observed data taken from a practical application. By using R, the whole procedure can be reproduced by the reader. All the data sets used in the book are available on the website http://staff.elena.aut.ac.nz/Paul-Cowpertwait/ts/. The book is written for undergraduate students of mathematics, economics, business and finance, geography, engineering and related disciplines, and postgraduate students who may need to analyse time series as part of their taught programme or their research.
Time Series For Data Science
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Author : Wayne A. Woodward
language : en
Publisher: CRC Press
Release Date : 2022-08-01
Time Series For Data Science written by Wayne A. Woodward and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-08-01 with Mathematics categories.
Data 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.
The Spectral Analysis Of Time Series
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Author : Lambert Herman Koopmans
language : en
Publisher:
Release Date : 1974
The Spectral Analysis Of Time Series written by Lambert Herman Koopmans and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1974 with Mathematics categories.
The Spectral Analysis of Time Series ...
Time Series
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Author : David R. Brillinger
language : en
Publisher:
Release Date : 1981
Time Series written by David R. Brillinger and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1981 with Mathematics categories.
The nature of time series and their frequency analysis. Foundations. Analytic properties of fourier transforms and complex matrices. Stochastic properties of finite fourier transforms. The estimation of power spectra. Analysis of a linear time invariant relation between a stochastic series and several deterministic series. Estimating the second-order spectra of vector-valued series. Analysis of a linear time invariant between two vector-valued stochastic series. Principal components in the frequency domain. The canonical analysis of time series. Proofs of theorems.