Using MANOVA and Semi-parametric Linear Mixed Effects Model for Traveling Vehicles Identification

• Main Authors: Chai-Tzu Yang, 楊茞慈
• Other Authors: Yow-Jen Jou
• Format: Others
• Language: zh-TW
• Online Access: http://ndltd.ncl.edu.tw/handle/33258647937593316636

碩士 === 國立交通大學 === 統計學研究所 === 95 === In order to make the detecting of the lanes and the types of the vehicles traveling on various roadways affordable, radio-frequency (RF) system-on-chip is designed and will be mounted on the roadside to collect vehicle information. The data originally collected by the chip is the intensity of the back wave of the vehicle entering the range of detection. The raw data is registered by landmark and then treated as functional data. In order to classify the types of the vehicles, two models are proposed to model the data. One is multivariate analysis of variance model to account for the main effect and the interaction effect between type and lane, the other is the semi-parametric linear model to emphasize the functional characteristic of the data. Both models work well when the number of groups is small but deteriorate when the number of groups increases.