基于rMDL、gMDL、nMDL、eMDL、AIC和BIC的非对称调整参数差异影响下的非对称价格传导线性模型的蒙特卡罗比较

遥感信息 Pub Date : 2019-12-20 DOI:10.1109/ICMRSISIIT46373.2020.9405827

I. K. Amponsah, H. Acquah

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引用次数: 0

摘要

研究了非对称调整对最小描述长度标准变体恢复真实数据生成过程能力的影响。在线性非对称价格传导模型框架内采用蒙特卡罗方法。实证结果表明，采用更复杂的模型或增加非对称调整参数的数量，可以提高模型选择方法对真实数据生成过程的恢复。最小描述长度准则在非对称价格传输模型中是非常可靠和有用的。为了获得最优的非对称价格传导线性模型，研究人员应该始终以更强的不对称水平为目标。

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A Monte Carlo Comparison of Asymmetric Price Transmission Linear Models Under the Effect of Difference in Asymmetric Adjustment Parameters using rMDL, gMDL, nMDL, eMDL, AIC & BIC

The effect of asymmetric adjustment on the ability of variants of minimum description length criteria was investigated in their ability to recover the true Data Generating Process. A Monte Carlo method was employed within the linear Asymmetric Price Transmission modelling framework. Results indicated empirically that application of a more complex model or increase in the number of asymmetric adjustment parameters improves the recovery of the true data generating process by the model selection methods. Minimum Description Length criteria are very reliable and useful in Asymmetric Price Transmission modelling. Researchers should always aim at stronger levels of asymmetry to achieve optimal Asymmetric Price Transmission linear models.

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来源期刊

遥感信息

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0.00%

发文量

3984

期刊介绍： Remote Sensing Information is a bimonthly academic journal supervised by the Ministry of Natural Resources of the People's Republic of China and sponsored by China Academy of Surveying and Mapping Science. Since its inception in 1986, it has been one of the authoritative journals in the field of remote sensing in China.In 2014, it was recognised as one of the first batch of national academic journals, and was awarded the honours of Core Journals of China Science Citation Database, Chinese Core Journals, and Core Journals of Science and Technology of China. The journal won the Excellence Award (First Prize) of the National Excellent Surveying, Mapping and Geographic Information Journal Award in 2011 and 2017 respectively. Remote Sensing Information is dedicated to reporting the cutting-edge theoretical and applied results of remote sensing science and technology, promoting academic exchanges at home and abroad, and promoting the application of remote sensing science and technology and industrial development. The journal adheres to the principles of openness, fairness and professionalism, abides by the anonymous review system of peer experts, and has good social credibility. The main columns include Review, Theoretical Research, Innovative Applications, Special Reports, International News, Famous Experts' Forum, Geographic National Condition Monitoring, etc., covering various fields such as surveying and mapping, forestry, agriculture, geology, meteorology, ocean, environment, national defence and so on. Remote Sensing Information aims to provide a high-level academic exchange platform for experts and scholars in the field of remote sensing at home and abroad, to enhance academic influence, and to play a role in promoting and supporting the protection of natural resources, green technology innovation, and the construction of ecological civilisation.