✦ LIBER ✦

Random Level-Shift Time Series Models, ARIMA Approximations, and Level-Shift Detection

✍ Scribed by Chung Chen and George C. Tiao

Book ID: 121396066
Publisher: American Statistical Association
Year: 1990
Tongue: English
Weight: 514 KB
Volume: 8
Category: Article
ISSN: 0735-0015
DOI: 10.2307/1391755

No coin nor oath required. For personal study only.

📜 SIMILAR VOLUMES

Detecting Level Shifts in Time Series

✍ Balke, Nathan S. 📂 Article 📅 1993 🏛 American Statistical Association 🌐 English ⚖ 464 KB

Detecting Level Shifts in Time Series

✍ Nathan S. Balke 📂 Article 📅 1993 🏛 American Statistical Association 🌐 English ⚖ 442 KB

Forecasting time series with long memory

Forecasting time series with long memory and level shifts

✍ Namwon Hyung; Philip Hans Franses 📂 Article 📅 2005 🏛 John Wiley and Sons 🌐 English ⚖ 97 KB

Detection of outliers and level shifts i

Detection of outliers and level shifts in time series: an evaluation of two alternative procedures

✍ Kjell Vaage 📂 Article 📅 2000 🏛 John Wiley and Sons 🌐 English ⚖ 180 KB

A uni®ed method to detect and handle innovational and additive outliers, and permanent and transient level changes has been presented by R. S. Tsay. N. S. Balke has found that the presence of level changes may lead to misidenti®cation and loss of test-power, and suggests augmenting Tsay's procedure

Level Shifts and the Illusion of Long Me

Level Shifts and the Illusion of Long Memory in Economic Time Series

✍ Smith, Aaron 📂 Article 📅 2005 🏛 American Statistical Association 🌐 English ⚖ 576 KB