Empirical Saddlepoint Approximations for Multivariate M- Estimators
|Published in||Journal of the Royal Statistical Society. B, Statistical Methodology. 1994, vol. 56, no. 2, p. 313-326|
|Abstract||In this paper, we investigate the use of the empirical distribution function in place of the underlying distribution function F to construct an empirical saddlepoint approximation to the density fn of a general multivariate M-estimator. We obtain an explicit form for the error term in the approximation, investigate the effect of renormalizing the estimator, carry out some numerical comparisons and discuss the regression problem.|
|Keywords||Bootstrap — M estimation — Estimator robustness — Linear regression — Probability density — Multivariate distribution — Asymptotic approximation — Saddle point — Renormalization — Small sample — Empirical distribution function|
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|RONCHETTI, Elvezio, WELSH, Alan H. Empirical Saddlepoint Approximations for Multivariate M- Estimators. In: Journal of the Royal Statistical Society. B, Statistical Methodology, 1994, vol. 56, n° 2, p. 313-326. https://archive-ouverte.unige.ch/unige:23215|