使用非常態state space model估計OD pattern

Abstract

在這篇論文中，我們提供一些方法去估計OD pattern。我們使用時間序列中的State Space model，並且考慮Non-Gaussian State Space model去估計參數。這些方法主要建立在Gibbs Sampler 和 Kalman Filter，最後將此方法應用於大眾捷運系統。

In this thesis we provide methods for estimating origin-destination demand pattern in the time domain. For doing this we use the state space model, and consider the non-Gaussian state space model to estimate parameters. These techniques rely on Gibbs sampler and Kalman filter. And we apply it to the rapid transit system.