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Author: Jiti Gao
Publisher:
ISBN:
Category : Markov processes
Languages : en
Pages :
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Book Description
This paper establishes several results for uniform convergence of nonparametric kernel density and regression estimates for the case where the time series regressors concerned are nonstationary null- recurrent Markov chains. Under suitable conditions, certain rates of convergence are also established for these estimates. Our results can be viewed as an extension of some well-known uniform consistency results for the stationary time series to the nonstationary time series case.
Author: Jiti Gao
Publisher:
ISBN:
Category : Markov processes
Languages : en
Pages :
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Book Description
This paper establishes several results for uniform convergence of nonparametric kernel density and regression estimates for the case where the time series regressors concerned are nonstationary null- recurrent Markov chains. Under suitable conditions, certain rates of convergence are also established for these estimates. Our results can be viewed as an extension of some well-known uniform consistency results for the stationary time series to the nonstationary time series case.
Author:
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ISBN:
Category :
Languages : en
Pages :
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Author: Jiti Gao
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Author: Jia Chen
Publisher:
ISBN:
Category : Asymptotic distribution (Probability theory)
Languages : en
Pages :
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Book Description
Estimation theory in a nonstationary environment has been very popular in recent years. Existing studies focus on nonstationarity in parametric linear, parametric nonlinear and nonparametric nonlinear models. In this paper, we consider a partially linear model of the form Yt = X t +g(Vt)+ t, t = 1, · · ·, n, where {Vt} is a sequence of -null recurrent Markov chains, {Xt} is a sequence of either strictly stationary or nonstationary regressors and { t} is a stationary sequence. We propose to estimate both a and g(·) semiparametrically. We then show that the proposed estimator of is still asymptotically normal with the same rate as for the case of stationary time series. We also establish the asymptotic normality for the nonparametric estimator of the function g(·) and the uniform consistency of the nonparametric estimator. The simulated example is given to show that our theory and method work well in practice.
Author: Thomas B. Fomby
Publisher: Emerald Group Publishing
ISBN: 1784411825
Category : Political Science
Languages : en
Pages : 772
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Book Description
This volume honors Professor Peter C.B. Phillips' many contributions to the field of econometrics. The topics include non-stationary time series, panel models, financial econometrics, predictive tests, IV estimation and inference, difference-in-difference regressions, stochastic dominance techniques, and information matrix testing.
Author: Hans Arnfinn Karlsen
Publisher:
ISBN:
Category :
Languages : en
Pages : 58
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Author: Sam Efromovich
Publisher: Springer Science & Business Media
ISBN: 0387987401
Category : Mathematics
Languages : en
Pages : 423
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Book Description
This book gives a systematic, comprehensive, and unified account of modern nonparametric statistics of density estimation, nonparametric regression, filtering signals, and time series analysis. The companion software package, available over the Internet, brings all of the discussed topics into the realm of interactive research. Virtually every claim and development mentioned in the book is illustrated with graphs which are available for the reader to reproduce and modify, making the material fully transparent and allowing for complete interactivity.
Author: H. D. Brunk
Publisher:
ISBN:
Category : Mathematics
Languages : en
Pages : 30
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Author: George Roussas
Publisher: Springer Science & Business Media
ISBN: 9780792312260
Category : Mathematics
Languages : en
Pages : 732
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Book Description
About three years ago, an idea was discussed among some colleagues in the Division of Statistics at the University of California, Davis, as to the possibility of holding an international conference, focusing exclusively on nonparametric curve estimation. The fruition of this idea came about with the enthusiastic support of this project by Luc Devroye of McGill University, Canada, and Peter Robinson of the London School of Economics, UK. The response of colleagues, contacted to ascertain interest in participation in such a conference, was gratifying and made the effort involved worthwhile. Devroye and Robinson, together with this editor and George Metakides of the University of Patras, Greece and of the European Economic Communities, Brussels, formed the International Organizing Committee for a two week long Advanced Study Institute (ASI) sponsored by the Scientific Affairs Division of the North Atlantic Treaty Organization (NATO). The ASI was held on the Greek Island of Spetses between July 29 and August 10, 1990. Nonparametric functional estimation is a central topic in statistics, with applications in numerous substantive fields in mathematics, natural and social sciences, engineering and medicine. While there has been interest in nonparametric functional estimation for many years, this has grown of late, owing to increasing availability of large data sets and the ability to process them by means of improved computing facilities, along with the ability to display the results by means of sophisticated graphical procedures.
Author: Shin Kanaya
Publisher:
ISBN:
Category :
Languages : en
Pages : 196
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