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Strongly consistent determination of cointegrating rank via canonical correlations
Poskitt, Donald Stephen - In: Journal of business & economic statistics : JBES ; a … 18 (2000) 1, pp. 77-90
Persistent link: https://www.econbiz.de/10001441609
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Performance of Johansen's cointegration test
Poh, Chee Wee; Tan, Randolph Gee Kwang - 1997
Persistent link: https://www.econbiz.de/10001500591
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The design of Monte Carlo experiments for VAR models
Dhrymes, Phoebus J. - 1996
Persistent link: https://www.econbiz.de/10000942998
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On the design of experiments when data are collected by passive observation
Jusélius, Katarina - 1991
Persistent link: https://www.econbiz.de/10000824074
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Predictive behavior : an experimental study
Brennscheidt, Gunnar - 1993
Persistent link: https://www.econbiz.de/10000877906
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An inductive logic programming approach to the classification of phases of business cycles
Morik, Katharina; Rüping, Stefan - In: Classification and clustering in business cycle analysis, (pp. 107-125). 2007
Persistent link: https://www.econbiz.de/10003410724
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Falsifying laboratory results through field tests : a time-series methodology and some results
Barta, Rajeev; Vanhonacker, Wilfred R. - In: Journal of business research : JBR 16 (1988) 4, pp. 281-300
Persistent link: https://www.econbiz.de/10003483415
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Expectation formation and regime switches
Becker, Otwin; Leitner, Johannes; Leopold-Wildburger, Ulrike - In: Experimental economics : a journal of the Economic … 12 (2009) 3, pp. 350-364
Persistent link: https://www.econbiz.de/10003877530
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An inductive logic programming approach to the classification of phases in business cycles
Morik, Katharina; Rüping, Stefan - 2002
A workbench for knowledge acquisition and data analysis is presented and its use for the classification of business cycles is investigated. Inductive Logic Programming (ILP) allows to model relations between intervals, e.g. time or value intervals. Moreover, the user of the workbench is...
Persistent link: https://www.econbiz.de/10009772052
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Finding or not finding rules in time series
Lin, Jessica; Keogh, Eamonn - In: Applications of artificial intelligence in finance and …, (pp. 175-201). 2004
Persistent link: https://www.econbiz.de/10002797349