Time Series+long Memory

Long‐Memory Time Series: Theory and Methods  eBooks & eLearning

Posted by AvaxGenius at Jan. 30, 2024
Long‐Memory Time Series: Theory and Methods

Long‐Memory Time Series: Theory and Methods by Wilfredo Palma
English | PDF | 2006 | 293 Pages | ISBN : 0470114029 | 36.7 MB

A self-contained, contemporary treatment of the analysis of long-range dependent data
Long-Memory Time Series: Theory and Methods provides an overview of the theory and methods developed to deal with long-range dependent data and describes the applications of these methodologies to real-life time series. Systematically organized, it begins with the foundational essentials, proceeds to the analysis of methodological aspects (Estimation Methods, Asymptotic Theory, Heteroskedastic Models, Transformations, Bayesian Methods, and Prediction), and then extends these techniques to more complex data structures.

Introduction to Time Series and Forecasting  eBooks & eLearning

Posted by AvaxGenius at Nov. 14, 2021
Introduction to Time Series and Forecasting

Introduction to Time Series and Forecasting by Peter J. Brockwell
English | PDF | 1996 | 429 Pages | ISBN : 0387947191 | 34.7 MB

Some of the key mathematical results are stated without proof in order to make the underlying theory acccessible to a wider audience. The book assumes a knowledge only of basic calculus, matrix algebra, and elementary statistics.

Introduction to Time Series and Forecasting  eBooks & eLearning

Posted by AvaxGenius at Aug. 7, 2023
Introduction to Time Series and Forecasting

Introduction to Time Series and Forecasting by Peter J. Brockwell, Richard A. Davis
English | PDF | 2002 | 443 Pages | ISBN : 1475777507 | 48.2 MB

Some of the key mathematical results are stated without proof in order to make the underlying theory accessible to a wider audience. The book assumes a knowledge only of basic calculus, matrix algebra, and elementary statistics. The emphasis is on methods and the analysis of data sets. The logic and tools of model-building for stationary and nonstationary time series are developed in detail and numerous exercises, many of which make use of the included computer package, provide the reader with ample opportunity to develop skills in this area.
The core of the book covers stationary processes, ARMA and ARIMA processes, multivariate time series and state-space models, with an optional chapter on spectral analysis. Additional topics include harmonic regression, the Burg and Hannan-Rissanen algorithms, unit roots, regression with ARMA errors, structural models, the EM algorithm, generalized state-space models with applications to time series of count data, exponential smoothing, the Holt-Winters and ARAR forecasting algorithms, transfer function models and intervention analysis. Brief introductions are also given to cointegration and to nonlinear, continuous-time and long-memory models.
The time series package included in the back of the book is a slightly modified version of the package ITSM, published separately as ITSM for Windows, by Springer-Verlag, 1994. It does not handle such large data sets as ITSM for Windows, but like the latter, runs on IBM-PC compatible computers under either DOS or Windows (version 3.1 or later). The programs are all menu-driven so that the reader can immediately apply the techniques in the book to time series data, with a minimal investment of time in the computational and algorithmic aspects of the analysis.

Discrete Time Series, Processes, and Applications in Finance (repost)  eBooks & eLearning

Posted by arundhati at July 2, 2020
Discrete Time Series, Processes, and Applications in Finance (repost)

Gilles Zumbach, "Discrete Time Series, Processes, and Applications in Finance "
English | ISBN: 3642317413 | 2013 | 322 pages | PDF | 23 MB

Time Series Analysis and Applications to Geophysical Systems: Part I  eBooks & eLearning

Posted by AvaxGenius at July 23, 2023
Time Series Analysis and Applications to Geophysical Systems: Part I

Time Series Analysis and Applications to Geophysical Systems: Part I by David R. Brillinger, Enders Anthony Robinson, Frederic Paik Schoenberg
English | PDF(True) | 262 Pages | ISBN : 0387978968 | 31.8 MB

Part of a two volume set based on a recent IMA program of the same name. The goal of the program and these books is to develop a community of statistical and other scientists kept up-to-date on developments in this quickly evolving and interdisciplinary field. Consequently, these books present recent material by distinguished researchers. Topics discussed in Part I include nonlinear and non- Gaussian models and processes (higher order moments and spectra, nonlinear systems, applications in astronomy, geophysics, engineering, and simulation) and the interaction of time series analysis and statistics (information model identification, categorical valued time series, nonparametric and semiparametric methods). Self-similar processes and long-range dependence (time series with long memory, fractals, 1/f noise, stable noise) and time series research common to engineers and economists (modeling of multivariate and possibly non-stationary time series, state space and adaptive methods) are discussed in Part II.

Python for Time Series Analysis: From Basics to Advanced Forecasting  eBooks & eLearning

Posted by TiranaDok at Oct. 15, 2024
Python for Time Series Analysis: From Basics to Advanced Forecasting

Python for Time Series Analysis: From Basics to Advanced Forecasting by Bharat Bhuval Nishad
English | September 24, 2024 | ISBN: N/A | ASIN: B0DHV3ZW4V | 54 pages | EPUB | 0.21 Mb

Time Series Analysis with Long Memory in View  eBooks & eLearning

Posted by roxul at Sept. 30, 2018
Time Series Analysis with Long Memory in View

Uwe Hassler, "Time Series Analysis with Long Memory in View"
English | ISBN: 1119470404 | 2018 | 288 pages | PDF | 3 MB

Long Memory in Economics (Repost)  eBooks & eLearning

Posted by step778 at Dec. 5, 2018
Long Memory in Economics (Repost)

Alan Kirman, Gilles Teyssière, Alan P. Kirman, "Long Memory in Economics"
2006 | pages: 392 | ISBN: 354022694X | PDF | 3,9 mb

Long-memory time series : theory and methods  eBooks & eLearning

Posted by insetes at March 23, 2019
Long-memory time series : theory and methods

Long-memory time series : theory and methods By Wilfredo Palma
2007 | 307 Pages | ISBN: 0470114029 | DJVU | 2 MB

Time Series Tokens: Foundations and Applications  eBooks & eLearning

Posted by lucky_aut at July 3, 2024
Time Series Tokens: Foundations and Applications

Time Series Tokens: Foundations and Applications
Last updated 6/2024
Duration: 47m | .MP4 1280x720, 30 fps(r) | AAC, 44100 Hz, 2ch | 789 MB
Genre: eLearning | Language: English

An Advanced Deep Dive Into Time Series Tokens And Neural Networks