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Series of Irregular Observations : Forecasting and Model Building
Overview of attention for book
Table of Contents
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Book Overview
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Chapter 1
Introduction
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Chapter 2
Discrete Time Random Processes
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Chapter 3
Gaussian Processes
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Chapter 4
Stationary Processes
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Chapter 5
Forecasting and Stationarity
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Chapter 6
Random Fields and Stochastic Integrals
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Chapter 7
Spectral Representation of Stationary Processes
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Chapter 8
Linear Filters
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Chapter 9
ARMA Processes and Processes with Rational Spectrum
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Chapter 10
Nonstationary ARMA Processes and Forecasting
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Chapter 11
Empirical Estimators and Periodograms
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Chapter 12
Empirical Estimation of the Parameters for Arma Processes with Rational Spectrum
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Chapter 13
Efficient Estimation for the Parameters of a Process with Rational Spectrum
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Chapter 14
Asymptotic Maximum Likelihood
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Chapter 15
Identification and Compensated Likelihood
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Chapter 16
A Few Problems not Studied Here
Overall attention for this book and its chapters
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institution with syllabi
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Book overview
1. Introduction
2. Discrete Time Random Processes
3. Gaussian Processes
4. Stationary Processes
5. Forecasting and Stationarity
6. Random Fields and Stochastic Integrals
7. Spectral Representation of Stationary Processes
8. Linear Filters
9. ARMA Processes and Processes with Rational Spectrum
10. Nonstationary ARMA Processes and Forecasting
11. Empirical Estimators and Periodograms
12. Empirical Estimation of the Parameters for Arma Processes with Rational Spectrum
13. Efficient Estimation for the Parameters of a Process with Rational Spectrum
14. Asymptotic Maximum Likelihood
15. Identification and Compensated Likelihood
16. A Few Problems not Studied Here
Summary
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Syllabi
Q&A
This data is correct as of December 2015 - for more up to date information, please visit
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So far, Altmetric has seen this research output assigned in
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syllabus from an institution on Open Syllabus Project.
Institution
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Course subject areas covered
Ruprecht-Karls-Universität Heidelberg
1
Biology, Education