Zobrazeno 1 - 10
of 160
pro vyhledávání: '"John Geweke"'
Autor:
John Geweke
Publikováno v:
Econometrics, Vol 4, Iss 1, p 10 (2016)
There is a one-to-one mapping between the conventional time series parameters of a third-order autoregression and the more interpretable parameters of secular half-life, cyclical half-life and cycle period. The latter parameterization is better suite
Externí odkaz:
https://doaj.org/article/f2271979fa8f425181d2679fd7c77cd1
Autor:
John Geweke
Econometric models are widely used in the creation and evaluation of economic policy in the public and private sectors. But these models are useful only if they adequately account for the phenomena in question, and they can be quite misleading if the
Autor:
John Geweke, Garland Durham
Publikováno v:
Journal of Econometrics. 210:4-25
The sequentially adaptive Bayesian learning algorithm (SABL) builds on and ties together ideas from sequential Monte Carlo and simulated annealing. The algorithm can be used to simulate from Bayesian posterior distributions, using either data temperi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a79be8a1ac7ed2edb24b8d162a0c4b1d
https://doi.org/10.1016/j.jeconom.2018.11.002
https://doi.org/10.1016/j.jeconom.2018.11.002
Autor:
John Geweke, Garland Durham
Publikováno v:
Advances in Info-Metrics
Rényi divergence is a natural way to measure the rate of information flow in contexts like Bayesian updating. This chapter shows how Monte Carlo integration can be used to measure Rényi divergence when (as is often the case) only kernels of the rel
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0b7fa095145ff49f613f15218ccf241e
https://doi.org/10.1093/oso/9780190636685.003.0015
https://doi.org/10.1093/oso/9780190636685.003.0015
Publikováno v:
Journal of Time Series Analysis. 40:388-410
This article develops practical methods for Bayesian inference in the autoregressive fractionally integrated moving average (ARFIMA) model using the exact likelihood function, any proper prior distribution, and time series that may have thousands of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8b4451b02d06d68ce4c895748bf56147
https://doi.org/10.1111/jtsa.12443
https://doi.org/10.1111/jtsa.12443
Autor:
Arimura, Toshi H. **I am grateful to Professors Edward Foster and John Geweke for their advice. I also thank Professors Jay Coggins, Thomas Holmes, Susumu Imai, Mark Roberts and Robert Cairns for their helpful suggestions. The comments and suggestions from the editor and three anonymous referees have helped me enhance the quality of the paper significantly. I also benefited from comments from Andrew Ching, Paul Sotkiewicz, John Winstandley and participants at the eighth Canadian Resource and Environmental Economics Study Group. All remaining errors are mine. This research was supported by a Walter Heller Fellowship. Address for correspondence: Department of Economics, Sophia University, 7-1 Kioi-cho, Chiyoda-ku, Tokyo, 102-8554 Japan. E-mail: t-arimu@sophia.ac.jp.
Publikováno v:
In Journal of Environmental Economics and Management September 2002 44(2):271-289
Publikováno v:
Journal of Financial Economics. 115:210-214
Christoffersen, Jacobs, and Ornthanalai (2012) (CJO) propose an interesting and useful class of generalized autoregressive conditional heteroskedasticity (GARCH)-like models with dynamic jump intensity, and find evidence that the models not only fit
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d9b2264c8b0d553bbadc40ade6b56589
https://doi.org/10.1016/j.jfineco.2014.08.004
https://doi.org/10.1016/j.jfineco.2014.08.004
Publikováno v:
International Journal of Research in Marketing. 31:35-48
This paper demonstrates a method for estimating logit choice models for small sample data, including single individuals, that is computationally simpler and relies on weaker prior distributional assumptions compared to hierarchical Bayes estimation.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0188f39864b6a8a91d5472e570d32b25
https://doi.org/10.1016/j.ijresmar.2013.07.005
https://doi.org/10.1016/j.ijresmar.2013.07.005
Autor:
Garland Durham, John Geweke
Publikováno v:
Journal of Financial Econometrics, 12(2), 278-306. Oxford University Press
This study considers three alternative sources of information about volatility potentially useful in predicting daily asset returns: past daily returns, past intraday returns, and a volatility index based on observed option prices. For each source of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a753ebb708076f797ad017fdf351e4ef
http://hdl.handle.net/10.1093/jjfinec/nbt001
http://hdl.handle.net/10.1093/jjfinec/nbt001