## Abstract A diagnostic procedure for detecting additive and innovation outliers as well as level shifts in a regression model with ARIMA errors is introduced. The procedure is based on a robust estimate of the model parameters and on innovation residuals computed by means of robust filtering. A M
✦ LIBER ✦
Robust estimation for linear regression with asymmetric errors
✍ Scribed by Ana M. Bianco; Marta Garcia Ben; Víctor J. Yohai
- Publisher
- John Wiley and Sons
- Year
- 2005
- Tongue
- French
- Weight
- 955 KB
- Volume
- 33
- Category
- Article
- ISSN
- 0319-5724
No coin nor oath required. For personal study only.
📜 SIMILAR VOLUMES
Outlier Detection in Regression Models w
✍
A. M. Bianco; M. García Ben; E. J. Martínez; V. J. Yohai
📂
Article
📅
2001
🏛
John Wiley and Sons
🌐
English
⚖ 130 KB
Robust Bayesian Inference for Seemingly
✍
Vee Ming Ng
📂
Article
📅
2002
🏛
Elsevier Science
🌐
English
⚖ 75 KB
Bayesian inference is considered for the seemingly unrelated regressions with an elliptically contoured error distribution. We show that the posterior distribution of the regression parameters and the predictive distribution of future observations under elliptical errors assumption are identical to
Change detection in linear regression wi
✍
Edit Gombay
📂
Article
📅
2009
🏛
John Wiley and Sons
🌐
French
⚖ 221 KB
Non-linear regression analysis with erro
✍
Georgia Valsami; Athanassios Iliadis; Panos Macheras
📂
Article
📅
2000
🏛
John Wiley and Sons
🌐
English
⚖ 250 KB
👁 3 views
Robust variance estimation in meta-regre
✍
Larry V. Hedges; Elizabeth Tipton; Matthew C. Johnson
📂
Article
📅
2010
🏛
John Wiley and Sons
🌐
English
⚖ 331 KB
Erratum: Robust variance estimation in m
✍
Larry V. Hedges; Elizabeth Tipton; Matthew C. Johnson
📂
Article
📅
2010
🏛
John Wiley and Sons
🌐
English
⚖ 46 KB