Redescending M-estimators in regression analysis, cluster analysis and image analysis Christine M¨ uller Carl von Ossietzky University Oldenburg Institute for Mathematics

Source URL: www.statistik.tu-dortmund.de

Asymptotic and Finite Sample Comparison of Two “Maximum Likelihood” Tail Index Estimators M. Ivette Gomes Universidade de Lisboa, Portugal

Source URL: www.cim.pt

Influence functions of trimmed likelihood estimators for lifetime experiments Sebastian Szugat ∗ TU Dortmund University Christine H. M¨uller

Source URL: www.statistik.tu-dortmund.de

M PRA Munich Personal RePEc Archive Finite Sample Properties of Tests Based on Prewhitened Nonparametric Covariance Estimators

Source URL: mpra.ub.uni-muenchen.de

Computing Chernoff ’s distribution Piet Groeneboom1 and Jon A. Wellner2 November 3, 1999 Abstract A distribution which arises in problems of estimation of monotone functions is that of the

Source URL: dutiosb.twi.tudelft.nl

• Statistical theory
• M-estimators
• Probability and statistics
• Normal distribution
• Maximum likelihood
• Heat equation
• Beta function
• Mean difference
• Statistics
• Mathematical analysis
• Estimation theory

Supplementary materials for this article are available online. Please go to www.tandfonline.com/r/JASA Generalized Jackknife Estimators of Weighted Average Derivatives Matias D. CATTANEO, Richard K. CRUMP, and Michael J

Source URL: eml.berkeley.edu

• Efficient estimator
• M-estimator
• Asymptotic theory
• Mean squared error
• Least squares
• Normal distribution
• Bayes estimator
• Statistics
• Estimation theory
• Estimator

Permutation estimation and minimax rates of identifiability Olivier Collier IMAGINE, Université Paris-Est hal, versionFeb 2013

Source URL: cbio.ensmp.fr

• Statistical inference
• M-estimators
• Combinatorics
• Maximum likelihood
• Consistent estimator
• Permutation
• Normal distribution
• Permutation pattern
• Statistics
• Estimation theory
• Statistical theory

Parameter-exploring Policy Gradients Frank Sehnkea , Christian Osendorfera , Thomas R¨ uckstießa , Alex Gravesa , Jan Petersc , J¨ urgen Schmidhubera,b a

Source URL: people.idsia.ch

• Statistical theory
• Statistics
• M-estimators
• Econometrics
• Science
• Engineering
• Maximum likelihood
• Estimation theory
• Dimensional analysis
• Measurement

Submitted to the Statistical Science A unified framework for high-dimensional analysis of M -estimators with decomposable regularizers

Source URL: www.eecs.berkeley.edu

• Econometrics
• Statistical inference
• Regression analysis
• Maximum likelihood
• Parametric model
• Linear regression
• Consistent estimator
• Matrix norm
• Loss function
• Statistics
• Estimation theory
• Statistical theory

Statistics 580 The EM Algorithm Introduction The EM algorithm is a very general iterative algorithm for parameter estimation by maximum likelihood when some of the random variables involved are not observed i.e., conside

Source URL: www.cse.cuhk.edu.hk

• M-estimators
• Expectation–maximization algorithm
• Missing data
• Maximum likelihood
• Sufficient statistic
• Statistics
• Estimation theory
• Statistical theory