A MISSING INFORMATION PRINCIPLE AND M-ESTIMATORS IN REGRESSION-ANALYSIS WITH CENSORED AND TRUNCATED DATA

被引:43
|
作者
LAI, TL [1 ]
YING, ZL [1 ]
机构
[1] RUTGERS STATE UNIV,DEPT STAT,NEW BRUNSWICK,NJ 08903
来源
ANNALS OF STATISTICS | 1994年 / 22卷 / 03期
关键词
M-ESTIMATOR; CENSORING; TRUNCATION; SELF-CONSISTENCY; LINEAR REGRESSION; MARTINGALE; ASYMPTOTIC NORMALITY; INFLUENCE FUNCTION; ROBUSTNESS;
D O I
10.1214/aos/1176325627
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
A general missing information principle is proposed for constructing M-estimators of regression parameters in the presence df left truncation and right censoring on the observed responses. By making use of martingale central limit theorems and empirical process theory, the asymptotic normality of M-estimators is established under certain assumptions. Asymptotically efficient M-estimators are also developed by using data-dependent score functions. In addition, robustness properties of the estimators are discussed and formulas for their influence functions are derived for the robustness analysis.
引用
收藏
页码:1222 / 1255
页数:34
相关论文
共 50 条
  • [31] ROBUST REGRESSION TREES BASED ON M-ESTIMATORS
    Galimberti, G.
    Pillati, M.
    Soffritti, G.
    STATISTICA, 2007, 67 (02) : 173 - 190
  • [32] Robust regression with projection based M-estimators
    Chen, HF
    Meer, P
    NINTH IEEE INTERNATIONAL CONFERENCE ON COMPUTER VISION, VOLS I AND II, PROCEEDINGS, 2003, : 878 - 885
  • [33] A NOTE ON THE UNIQUENESS OF M-ESTIMATORS IN ROBUST REGRESSION
    CRISP, A
    BURRIDGE, J
    CANADIAN JOURNAL OF STATISTICS-REVUE CANADIENNE DE STATISTIQUE, 1993, 21 (02): : 205 - 208
  • [34] EDGEWORTH EXPANSIONS FOR M-ESTIMATORS OF A REGRESSION PARAMETER
    LAHIRI, SN
    JOURNAL OF MULTIVARIATE ANALYSIS, 1992, 43 (01) : 125 - 132
  • [35] Regression depth with censored and truncated data
    Park, J
    Hwang, J
    COMMUNICATIONS IN STATISTICS-THEORY AND METHODS, 2003, 32 (05) : 997 - 1008
  • [36] M-estimators of location for functional data
    Sinova, Beatriz
    Gonzalez-Rodriguez, Gil
    Van Aelst, Stefan
    BERNOULLI, 2018, 24 (03) : 2328 - 2357
  • [37] A smoothing principle for the Huber and other location M-estimators
    Hampel, Frank
    Hennig, Christian
    Ronchetti, Elvezio
    COMPUTATIONAL STATISTICS & DATA ANALYSIS, 2011, 55 (01) : 324 - 337
  • [38] PAIRWISE DIFFERENCE ESTIMATORS OF CENSORED AND TRUNCATED REGRESSION-MODELS
    HONORE, BE
    POWELL, JL
    JOURNAL OF ECONOMETRICS, 1994, 64 (1-2) : 241 - 278
  • [39] INVARIANCE PRINCIPLE IN REGRESSION-ANALYSIS
    BHATTACHARYA, PK
    ANNALS OF STATISTICS, 1976, 4 (03): : 621 - 624
  • [40] PRINCIPAL COMPONENT ESTIMATORS IN REGRESSION-ANALYSIS
    CHENG, DC
    IGLARSH, HJ
    REVIEW OF ECONOMICS AND STATISTICS, 1976, 58 (02) : 229 - 234