Robust Nonparametric Function Estimation with Serially Correlated Data
Author : Yijia Feng
Publisher :
Page : 137 pages
File Size : 34,89 MB
Release : 2011
Category :
ISBN :
Author : Yijia Feng
Publisher :
Page : 137 pages
File Size : 34,89 MB
Release : 2011
Category :
ISBN :
Author : Peter Hackl
Publisher : Springer Science & Business Media
Page : 495 pages
File Size : 16,87 MB
Release : 2013-03-09
Category : Business & Economics
ISBN : 366202571X
In 1984, the University of Bonn (FRG) and the International Institute for Applied System Analysis (IIASA) in Laxenburg (Austria), created a joint research group to analyze the relationship between economic growth and structural change. The research team was to examine the commodity composition as well as the size and direction of commodity and credit flows among countries and regions. Krelle (1988) reports on the results of this "Bonn-IIASA" research project. At the same time, an informal IIASA Working Group was initiated to deal with prob lems of the statistical analysis of economic data in the context of structural change: What tools do we have to identify nonconstancy of model parameters? What type of models are particularly applicable to nonconstant structure? How is forecasting affected by the presence of nonconstant structure? What problems should be anticipated in applying these tools and models? Some 50 experts, mainly statisticians or econometricians from about 15 countries, came together in Lodz, Poland (May 1985); Berlin, GDR (June 1986); and Sulejov, Poland (September 1986) to present and discuss their findings. This volume contains a selected set of those conference contributions as well as several specially invited chapters.
Author : Mathematical Sciences Research Institute (Berkeley, Calif.).
Publisher :
Page : 21 pages
File Size : 16,32 MB
Release : 1992
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ISBN :
Author : Ke-Li Xu
Publisher :
Page : 27 pages
File Size : 28,88 MB
Release : 2014
Category :
ISBN :
In this paper we consider the deterministic trend model where the error process is allowed to be weakly or strongly correlated and subject to nonstationary volatility. Extant estimators of the trend coefficient are analyzed. We find that under heteroskedasticity the Cochrane-Orcutt-type estimator (with some initial condition) could be less efficient than OLS when the process is highly persistent, while it is asymptotically equivalent to OLS when the process is less persistent. An efficient nonparametrically weighted Cochrane-Orcutt-type estimator is then proposed. The efficiency is uniform over weak or strong serial correlation and non-stationary volatility of unknown form. The feasible estimator relies on nonparametric estimation of the volatility function, and the asymptotic theory is provided. We use the data-dependent smoothing bandwidth that can automatically adjust for the strength of nonstationarity in volatilities. The implementation does not require pretesting persistence of the process or specification of nonstationary volatility. Finite-sample evaluation via simulations and an empirical application demonstrates the good performance of proposed estimators.
Author : Lazlo Györfi
Publisher : Springer
Page : 157 pages
File Size : 16,46 MB
Release : 2013-12-21
Category : Mathematics
ISBN : 146123686X
Because of the sheer size and scope of the plastics industry, the title Developments in Plastics Technology now covers an incredibly wide range of subjects or topics. No single volume can survey the whole field in any depth and what follows is, therefore, a series of chapters on selected topics. The topics were selected by us, the editors, because of their immediate relevance to the plastics industry. When one considers the advancements of the plastics processing machinery (in terms of its speed of operation and conciseness of control), it was felt that several chapters should be included which related to the types of control systems used and the correct usage of hydraulics. The importance of using cellular, rubber-modified and engineering-type plastics has had a major impact on the plastics industry and therefore a chapter on each of these subjects has been included. The two remaining chapters are on the characterisation and behaviour of polymer structures, both subjects again being of current academic or industrial interest. Each of the contributions was written by a specialist in that field and to them all, we, the editors, extend our heartfelt thanks, as writing a contribution for a book such as this, while doing a full-time job, is no easy task.
Author : Yves Croissant
Publisher : John Wiley & Sons
Page : 328 pages
File Size : 47,68 MB
Release : 2018-08-10
Category : Mathematics
ISBN : 1118949188
Panel Data Econometrics with R provides a tutorial for using R in the field of panel data econometrics. Illustrated throughout with examples in econometrics, political science, agriculture and epidemiology, this book presents classic methodology and applications as well as more advanced topics and recent developments in this field including error component models, spatial panels and dynamic models. They have developed the software programming in R and host replicable material on the book’s accompanying website.
Author :
Publisher :
Page : 8 pages
File Size : 37,37 MB
Release : 1991
Category :
ISBN :
Our research efforts can be broken down into three categories: (1) smoothing dependent data, (2) general issues arising in function estimation, and (3) hypothesis testing based on smoothing methods.
Author : Torben Gustav Andersen
Publisher : Springer Science & Business Media
Page : 1045 pages
File Size : 36,57 MB
Release : 2009-04-21
Category : Business & Economics
ISBN : 3540712976
The Handbook of Financial Time Series gives an up-to-date overview of the field and covers all relevant topics both from a statistical and an econometrical point of view. There are many fine contributions, and a preamble by Nobel Prize winner Robert F. Engle.
Author : Jeffrey Racine
Publisher : Oxford University Press
Page : 562 pages
File Size : 17,34 MB
Release : 2013-12-31
Category : Business & Economics
ISBN : 0199857954
This volume, edited by Jeffrey Racine, Liangjun Su, and Aman Ullah, contains the latest research on nonparametric and semiparametric econometrics and statistics. These data-driven models seek to replace the classical parametric models of the past, which were rigid and often linear. Chapters by leading international econometricians and statisticians highlight the interface between econometrics and statistical methods for nonparametric and semiparametric procedures. They provide a balanced view of new developments in the modeling of cross-section, time series, panel, and spatial data. Topics of the volume include: the methodology of semiparametric models and special regressor methods; inverse, ill-posed, and well-posed problems; methodologies related to additive models; sieve regression, nonparametric and semiparametric regression, and the true error of competing approximate models; support vector machines and their modeling of default probability; series estimation of stochastic processes and their application in Econometrics; identification, estimation, and specification problems in semilinear time series models; nonparametric and semiparametric techniques applied to nonstationary or near nonstationary variables; the estimation of a set of regression equations; and a new approach to the analysis of nonparametric models with exogenous treatment assignment.
Author : Sneh Gulati
Publisher :
Page : 124 pages
File Size : 42,40 MB
Release : 1991
Category : Data editing
ISBN :