Using PLS Regression and ECM for Estimating Freight Transport Demand in Tunisia

被引：0
|
作者：
Bouguerra, Hajera [1 ]
Souissi, Besma [2 ]
Benammou, Saloua [1 ]
机构：
[1] Univ Sousse, Fac Sci Econ & Gest, Sousse, Tunisia
[2] Univ Monastir, Fac Sci, Computat Math Lab, Monastir, Tunisia
来源：
INNOVATION AND SUSTAINABLE COMPETITIVE ADVANTAGE: FROM REGIONAL DEVELOPMENT TO WORLD ECONOMIES, VOLS 1-5 | 2012年
关键词：
Road freight transport; ECM; PLS regression;
D O I：
暂无
中图分类号：
F [经济];
学科分类号：
02 ;
摘要：
In this study we attempt to estimate the road freight transport demand in Tunisia by two regression methods: the error correction model (ECM) which takes into account the problem of stationary and the Partial least squares regression (PLS) which allows the estimation of this demand despite the strong correlation between variables and show empirically the superiority of this last one.
引用
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页码：517 / +
页数：3
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