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13 Basic nonparametric estimates

Timo Teräsvirta, Dag Tjøstheim, and W. J. Granger

in Modelling Nonlinear Economic Time Series

Published in print:
2010
Published Online:
May 2011
ISBN:
9780199587148
eISBN:
9780191595387
Item type:
chapter
Publisher:
Oxford University Press
DOI:
10.1093/acprof:oso/9780199587148.003.0013
Subject:
Economics and Finance, Econometrics

There are several books on the topics treated in this chapter. For completeness and ease of reference, in the present chapter a brief summary of some results in this area is presented. Among other ... More


Entropy-Based Model Averaging Estimation of Nonparametric Models

Yundong Tu

in Advances in Info-Metrics: Information and Information Processing across Disciplines

Published in print:
2020
Published Online:
December 2020
ISBN:
9780190636685
eISBN:
9780190636722
Item type:
chapter
Publisher:
Oxford University Press
DOI:
10.1093/oso/9780190636685.003.0018
Subject:
Economics and Finance, Microeconomics

In this chapter, I propose a model averaging estimation of nonparametric models based on Shannon’s entropy measure. The choice of weights in the averaging estimator is implemented bya maximizing the ... More


11 Nonlinear and nonstationary models

Timo Teräsvirta, Dag Tjøstheim, and W. J. Granger

in Modelling Nonlinear Economic Time Series

Published in print:
2010
Published Online:
May 2011
ISBN:
9780199587148
eISBN:
9780191595387
Item type:
chapter
Publisher:
Oxford University Press
DOI:
10.1093/acprof:oso/9780199587148.003.0011
Subject:
Economics and Finance, Econometrics

Long memory, unit root models and cointegration are important in linear modelling of nonstationary processes, not the least in econometrics. Recently, nonlinear generalizations of these concepts have ... More


Linear-Gaussian systems and signal processing

Max A. Little

in Machine Learning for Signal Processing: Data Science, Algorithms, and Computational Statistics

Published in print:
2019
Published Online:
October 2019
ISBN:
9780198714934
eISBN:
9780191879180
Item type:
chapter
Publisher:
Oxford University Press
DOI:
10.1093/oso/9780198714934.003.0007
Subject:
Mathematics, Logic / Computer Science / Mathematical Philosophy, Mathematical Physics

Linear systems theory, based on the mathematics of vector spaces, is the backbone of all “classical” DSP and a large part of statistical machine learning. The basic idea -- that linear algebra ... More


Statistical modelling and inference

Max A. Little

in Machine Learning for Signal Processing: Data Science, Algorithms, and Computational Statistics

Published in print:
2019
Published Online:
October 2019
ISBN:
9780198714934
eISBN:
9780191879180
Item type:
chapter
Publisher:
Oxford University Press
DOI:
10.1093/oso/9780198714934.003.0004
Subject:
Mathematics, Logic / Computer Science / Mathematical Philosophy, Mathematical Physics

The modern view of statistical machine learning and signal processing is that the central task is one of finding good probabilistic models for the joint distribution over all the variables in the ... More


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