- 期刊
Do Copulas Improve an Efficiency of Seemingly Unrelated Regression Model?
並列摘要
The conventional SUR model has a strong assumption of normally distributed residuals which might not be realistic. What this paper suggests is to take an advantage from Copulas approach in order to relax this normality assumption. Therefore, we introduce the Copulabased SUR model as an alternative to the conventional SUR model. The performance and accuracy of the proposed model are evaluated through the simulation study. We then apply the Copula-based SUR model to the real data set of Thai rubber and compare the estimation result with the result obtained from the conventional SUR model. The results of this paper could support our suggestion that the Copulas can be used appropriately to relax the assumption of normality of residuals in the conventional SUR model.
延伸閱讀
- 高子瑗（2015）。Effect Regression Analysis〔碩士論文，國立交通大學〕。華藝線上圖書館。https://doi.org/10.6842/NCTU.2015.00239
- 莊承儒（2018）。Influential Point Analysis in Regression Model〔碩士論文，中原大學〕。華藝線上圖書館。https://doi.org/10.6840/cycu201800847
- Wang, S., Shi, Y., & Su, L. (2014). Weaker Regularity Conditions and Sparse Recovery in High-Dimensional Regression. Journal of Applied Mathematics, 2014(), 608-614-953. https://doi.org/10.1155/2014/946241
- 張簡郁煒（2019）。Cumulative Logistic Regression Analysis of Ordinal Response〔碩士論文，淡江大學〕。華藝線上圖書館。https://www.airitilibrary.com/Article/Detail?DocID=U0002-1508201910155200
- 趙德芳（2008）。Applying Regression Model Correctly In Various Experiment Goal〔碩士論文，淡江大學〕。華藝線上圖書館。https://doi.org/10.6846/TKU.2008.00842