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عنوان فارسی مقاله:
مدل سازی تاخیر احتمالی نامتقارن ورود هواپیما
عنوان انگلیسی مقاله:
Modelling the asymmetric probabilistic delay of aircraft arrival
سال انتشار : 2017
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بخشی از مقاله انگلیسی:
2. Methodology: logistic models
2.1. Classical models Logistic regression has long been the standard method for studying the relationship between a binary response variable and one or more predictors or explanatory variables, using a cumulative density function (cdf), termed J. Let x be a vector of explanatory variables and y the response variable taking values in f0; 1g. This can be expressed as Prðy ¼ 1jx; bÞ ¼ Jðx0 bÞ. Then, by taking J as the cdf of the logistic distribution, we obtain the logistic regression. In this case, the probability density function is symmetric about zero. Thus, the cdf approaches 1 at the same rate as it approaches 0. However, in many practical situations this is not a reasonable outcome, because data are often positively or negatively skewed and contain a substantial proportion of zeros (nonezeros) with respect to the proportion of nonezeros (zeros). This asymmetry may arise in diverse practical situations and then the logit model is not really appropriate. Since the pioneering study by Prentice (1976), various new models of dichotomous choice have been proposed to overcome this problem (under logit and probit assumptions), greatly assisted by advances in computer technology and software development. See, for example, Stukel (1988, 1990), Chen et al. (1999), Fernandez and Steel (1998), Fletcher et al. (2005), Bazan et al. (2006, 2010) and Kumar and Manju (2015). As observed by Stukel (1988) and Chen et al. (1999), the use of an asymmetric link function is recommended for binary response data when one response is much more frequent than the other.
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کلمات کلیدی:
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