LOCAL LIKELIHOOD-BASED ON KERNEL CENSORING

• 成果类型: Article
• 署名作者: COPAS, JB
• 刊物名称: JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY
• ISSN/ISSBN: 1369-7412
• 发表日期: 1995
• 页码: 221-235
• 关键词: DENSITY-ESTIMATION

摘要

By drawing an analogy with likelihood for censored data, a local likelihood function is proposed which gives more weight to observations near a region of interest in the sample space. Resulting methods can be used for assessing local departures from a parametric model, and for semiparametric density estimation. Some theory, and three examples, is given.