The Analysis of Time Series: An Introduction

The Analysis of Time Series: An Introduction, Fifth Edition  eBooks & eLearning

Posted by lenami at Oct. 24, 2010
The Analysis of Time Series: An Introduction, Fifth Edition

The Analysis of Time Series: An Introduction, Fifth Edition
Publisher: Chapman & Hall | ISBN: 0412716402 | edition 1996 | PDF | 304 pages | 12 mb

"As an introduction to techniques for analyzing discrete time series, this textbook explains probability models, the spectral density function, time-invariant linear systems, state-space models, nonlinear models, and multivariate time series models."-"Book News, Inc."
This tidy book is a highly readable, introductory survey to the topic of modern time series analysis. It excels in its ability to focus on the more intuitive aspects of analysis and model identification. The discussion of both time- and frequency-domain approaches is reasonably balanced, and Kalman filtering is also introduced.
Fourier Analysis of Time Series: An Introduction, 2nd edition (Repost)

Peter Bloomfield, "Fourier Analysis of Time Series: An Introduction, 2nd edition"
English | 2000 | ISBN: 0471889482 | 288 pages | PDF | 3,2 MB
Fourier Analysis of Time Series: An Introduction, 2nd edition (repost)

Peter Bloomfield, "Fourier Analysis of Time Series: An Introduction, 2nd edition"
2000 | ISBN: 0471889482 | 288 pages | PDF | 3,2 MB

The Metapsychology of Christopher Bollas: An Introduction  eBooks & eLearning

Posted by interes at Nov. 19, 2016
The Metapsychology of Christopher Bollas: An Introduction

The Metapsychology of Christopher Bollas: An Introduction by Sarah Nettleton
English | 2016 | ISBN: 1138795550, 1138795542 | 128 pages | PDF | 10,7 MB
Analysis of Time Series Structure: SSA and related techniques by Vladimir Nekrutkin

Analysis of Time Series Structure: SSA and related techniques by Vladimir Nekrutkin
English | Jan 23, 2001 | ISBN: 1584881941 | 309 Pages | PDF | 4 MB

Over the last 15 years, singular spectrum analysis (SSA) has proven very successful. It has already become a standard tool in climatic and meteorological time series analysis and well known in nonlinear physics and signal processing.
Hidden Markov Models for Time Series: An Introduction Using R [Repost]

Walter Zucchini, Iain L. MacDonald - Hidden Markov Models for Time Series: An Introduction Using R
Published: 2009-04-28 | ISBN: 1584885734 | PDF | 269 pages | 2 MB
Analysis of Aircraft Structures: An Introduction, 2 edition (repost)

Analysis of Aircraft Structures: An Introduction, 2 edition by Bruce K. Donaldson
English | ISBN: 0521865832 | 2008 | PDF | 974 pages | 17,6 MB

As with the first edition, this textbook provides a clear introduction to the fundamental theory of structural analysis as applied to vehicles, aircraft, spacecraft, automobiles, and ships. The emphasis is on the application of fundamental concepts of structural analysis in everyday engineering practice. No assumptions are made with regard to the method of analysis.
Extracting Knowledge From Time Series: An Introduction to Nonlinear Empirical Modeling (Repost)

Boris P. Bezruchko, Dmitry A. Smirnov, "Extracting Knowledge From Time Series: An Introduction to Nonlinear Empirical Modeling"
English | 2010 | ISBN: 3642126006 | 420 pages | PDF | 14 MB
Hidden Markov Models for Time Series: An Introduction Using R (Monographs on Statistics and Applied Probability)

Hidden Markov Models for Time Series
Walter Zucchini, Iain L. MacDonald | Chapman & Hall/CRC | 2009-04-28 | ISBN:1584885734 | Pages: 269 | PDF | 5.3MB

This book illustrates the wonderful flexibility of HMMs as general-purpose models for time series data. It presents an accessible overview of HMMs for analyzing time series data, from continuous-valued, circular, and multivariate series to binary data, bounded and unbounded counts, and categorical observations. It explores a variety of applications in animal behavior, finance, epidemiology, climatology, and sociology. The authors discuss how to employ the freely available computing environment R to carry out computations for parameter estimation, model selection and checking, decoding, and forecasting. They provide all of the data sets analyzed in the text online.

The elements of artificial intelligence: An introduction using LISP

The elements of artificial intelligence: An introduction using LISP (Principles of computer science series) By S Tanimoto
Publisher: Computer Science Press 2006 | 530 Pages | ISBN: 0881751138 | PDF | 27 MB