105年第1學期-1761 時間序列 課程資訊

評分方式

評分項目	配分比例	說明
Attendance	10
Quiz 1 (期中考前)	15
Quiz 2 (期中考後)	15
Midterm Exam	20
分組期末報告 (口頭報告及PPT)	20

教育目標

就課程概述所規畫之課程內容範疇，以大學部學生為授課對象，因此課程目標上將比課程概述所規畫之課程內容範疇較為應用及方法上的理解及對資料方面的分析與建模。理論的部份以大學部學生所受之基礎訓練下，僅限於關鍵方法與模型上主要推導為主。 課程目標: 建立對時間序列模型及方法的觀念與應用 能對時間序列資料進行一般的分析 使用R語言分析時間序列 課程內容包含以下: Time series data Stationary time series ARMAmodels Estimation of ARMA models Forecasting

課程概述

A time series is a sequence of observations that are arranged according to the time of their outcome. Many recent applications of time series receive much of attention in financial areas. However, time series analysis has also exhibited its importance across many scientific areas for a long history and the desire of such analysis is still going on. This course is to provide introductory lessons in time series for the third and fourth year of undergraduates, who have major interests in statistics, and have finished some elementary courses, such as statistics, calculus, linear algebra and regression. The courses will be in three parts. The first part will be on the focus of regression, including a quick overall review of basics and an extension of regression modeling particularly required for time series data. The second part is aimed at the ARIMA models and seasonal models, which are traditional treatments established by Box and Jenkins. The third part is to introduce some new advances in time series or more real applications of time series models. Served as an undergraduate course, the topics will not be expected to go in great depth but to learn basic approach and to prepare background for further advanced studies.

基本資料

選修課，學分數：3-0
上課時間：一/5[M116] 二/7,8[M120]
修課班級：統計系2-4
修課年級：年級以上
選課備註：大數據資料群組(105適用),A群組(101-104適用)

參考書目

Introduction to Time Series and Forecasting (Springer Texts in Statistics) Hardcover – April 29, 2010
by Peter J. Brockwell (Author), Richard A. Davis (Author)