Zobrazeno 1 - 10
of 85
pro vyhledávání: '"David A. Belsley"'
Autor:
David A. Belsley, A. M. Robert Taylor, Kenneth Judd, Francis X. Diebold, Siem Jan Koopman, Eric Jacquier, H. Peter Boswijk, Erricos John Kontoghiorghes, Willi Semmler, Christian Francq, Robert F. Engle, Herman K. van Dijk, David Pollock, Tommaso Proietti, John M. Maheu, Michael H. P. West, Richard Smith, Hashem Pesaran, Carl Chiarella, Ana Colubi, Alessandra Amendola, Alessandra Luati, Cathy W. S. Chen, Qiwei Yao, Tim Bollerslev, Andrew Harvey, Marc Hallin, Jean-Michel Zakoian, Mark F. J. Steel, Elias Tzavalis, James G. MacKinnon, Gary Koop, Peter C.B. Phillips, Manfred Deistler, Olivier Scaillet, Yasuhiro Omori, Monica Billio, Jean-Marie Dufour, Helmut Lütkepohl, Mike K. P. So, Stefan Mittnik, Jeroen V.K. Rombouts
Publikováno v:
Computational Statistics & Data Analysis. 76:1-3
Publikováno v:
Computational Statistics & Data Analysis. 44:3-35
The computational efficiency of various algorithms for solving seemingly unrelated regressions (SUR) models is investigated. Some of the algorithms adapt known methods; others are new. The first transforms the SUR model to an ordinary linear model an
Publikováno v:
Climate Research. 24:15-18
Lower tropospheric temperature anomalies from the global satellite MSU that have been available since 1979 are unique and play a significant role in the continuing climate debate. A number of investigators have analyzed the MSU data using regression
Autor:
David A. Belsley
Publikováno v:
Journal of Economic Dynamics and Control. 26:1379-1396
The traditional two-step procedure for correcting for heteroskedasticity uses a consistent but biased estimator for the variances $\bfg\sigma_t^2$ in enacting the second step. An estimator is developed here that is unbiased in the presence of heteros
Autor:
David A. Belsley
Publikováno v:
Computational Economics. 14:69-87
Today‘s graduate students in economics must master early on a computational environment suitable for their research needs. A case is made here why Mathematica is an eminently reasonable choice for this purpose for many students. Salient features of
Autor:
David A. Belsley
Publikováno v:
Computational Economics. 10:197-229
Monte Carlo experiments establish that the usual ’t-statistic‘ used for testing for first-order serial correlation with artificial regressions is far from being distributed as a Student‘s t in small samples. Rather, it is badly biased in both m
Publikováno v:
Computational Statistics & Data Analysis. 49:283-285
Autor:
David A. Belsley
Publikováno v:
Computational Economics. 9:181-198
Artificial regression allows a simple and flexible test of serial correlation with many virtues that promote it, in principle, to a position of dominance. But it has a serious small-sample problem: successively truncated lagged residual regressors re
Autor:
David A. Belsley, Cathy W.S. Chen, Christian Francq, Giampiero Gallo, Lynda Khalaf, Erricos John Kontoghiorghes, Herman K. van Dijk
The journal Computational Statistics and Data Analysis has had five regular issues dedicated to computational econometrics (Belsley and Kontoghiorghes, 2003, Belsley and Kontoghiorghes, 2005, Belsley et al., 2007, Belsley et al., 2009, Belsley et al.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a802178ad76f58834200d85f419d3054
https://hdl.handle.net/20.500.14279/14734
https://hdl.handle.net/20.500.14279/14734