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


文件中的檔案:

  1. 000322670200012.pdf