Browsing by Author "Jea, R"

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Correlation and the time interval in multiple regression models
(2005-04-16)
Jea, R
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Lin, JL
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Su, CT
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工業工程與管理學系
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Department of Industrial Engineering and Management
In this paper we investigate the time interval effect of multiple regression models in which some of the variables are additive and some are multiplicative. The effect on the partial regression and correlation coefficients is influenced by the selected time interval. We find that the partial regression and correlation coefficients between two additive variables approach one-period values as n increases. When one of the variables is multiplicative, they will approach zero in the limit. We also show that the decreasing speed of the n-period correlation coefficients between both multiplicative variables is faster than others, except that a one-period correlation has a higher positive value. The results of this paper can be widely applied in various fields where regression or correlation analyses are employed. (C) 2003 Elsevier B.V. All rights reserved.
Time aggregation effect on the correlation coefficient: added-systematically sampled framework
(2005-11-01)
Jea, R
;
Su, CT
;
Lin, JL
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交大名義發表
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National Chiao Tung University
The aggregation of financial and economic time series occurs in a number of ways. Temporal aggregation or systematic sampling is the commonly used approach. In this paper, we investigate the time interval effect of multiple regression models in which the variables are additive or systematically sampled. The correlation coefficient changes with the selected time interval when one is additive and the other is systematically sampled. It is shown that the squared correlation coefficient decreases monotonically as the differencing interval increases, approaching zero in the limit. When two random variables are both added or systematically sampled, the correlation coefficient is invariant with time and equal to the one-period values. We find that the partial regression and correlation coefficients between two additive or systematically sampled variables approach one-period values as n increases. When one of the variables is systematically sampled, they will approach zero in the limit. The time interval for the association analyses between variables is not selected arbitrarily or the statistical results are likely affected.