標題: | Multiple deletion diagnostics in beta regression models |
作者: | Chien, Li-Chu 統計學研究所 Institute of Statistics |
關鍵字: | Beta regression;Multiple outliers;Generalized SWR;Generalized LD;Generalized DFFITS;Generalized DFBETAS |
公開日期: | 1-八月-2013 |
摘要: | We consider the problem of identifying multiple outliers in a general class of beta regression models proposed by Ferrari and Cribari-Neto (J Appl Stat 31:799-815, 2004). The currently available single-case deletion diagnostic measures, e.g., the standardized weighted residual (SWR), the Cook-like distance (LD), etc., often fail to identify multiple outlying observations, because they suffer from the well-known problems of masking and swamping effects. In this article, we develop group deletion diagnostic measures, such as generalized SWR, generalized LD, generalized DFFITS and generalized DFBETAS, and suggest a simple procedure for identifying multiple outliers using these. The performance of the proposed methods is investigated through simulation studies and two practical examples. |
URI: | http://dx.doi.org/10.1007/s00180-012-0370-9 http://hdl.handle.net/11536/22122 |
ISSN: | 0943-4062 |
DOI: | 10.1007/s00180-012-0370-9 |
期刊: | COMPUTATIONAL STATISTICS |
Volume: | 28 |
Issue: | 4 |
起始頁: | 1639 |
結束頁: | 1661 |
顯示於類別: | 期刊論文 |