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M-estimator
Results: 410

#	Item
71	NONPARAMETRIC REGRESSION IN IMAGING: FROM LOCAL KERNEL TO MULTIPLE-MODEL NONLOCAL COLLABORATIVE FILTERING Vladimir Katkovnik, Alessandro Foi, Karen Egiazarian, and Jaakko Astola Department of Signal Processing, Tampere U Add to Reading List Source URL: ticsp.cs.tut.fi Language: English - Date: 2008-09-03 07:24:05 Regression analysis Econometrics Image denoising Spatial data analysis Nonparametric regression Kernel regression Mutual information M-estimator Statistics Non-parametric statistics Estimation theory
72	Microsoft Word - Abstract_Tyler Add to Reading List Source URL: www.statistik.tu-dortmund.de Language: English - Date: 2014-09-19 05:11:47 Robust statistics Variance Estimator Scatter matrix Sample mean and sample covariance MINQUE Shrinkage estimator Statistics Estimation theory M-estimator
73	ESTIMATION THEORY AND INFORMATION GEOMETRY BASED ON DENOISING Aapo Hyv¨arinen Dept of Computer Science, Dept of Mathematics & Statistics, and HIIT University of Helsinki, Finland. ABSTRACT We consider a new estimation m Add to Reading List Source URL: sp.cs.tut.fi Language: English - Date: 2008-08-06 07:07:00 Fisher information Parametric model Estimator Linear regression Score Efficient estimator M-estimator Statistics Estimation theory Maximum likelihood
74	A Score Based Approach to Wild Bootstrap Inference Patrick Kline Andres Santos∗ Add to Reading List Source URL: eml.berkeley.edu Language: English - Date: 2011-08-05 15:02:00 Statistical theory Regression analysis Parametric statistics Bootstrapping Resampling M-estimator Pivotal quantity Ordinary least squares T-statistic Statistics Estimation theory Statistical inference
75	Submitted to the Statistical Science A unified framework for high-dimensional analysis of M -estimators with decomposable regularizers Add to Reading List Source URL: www.eecs.berkeley.edu Language: English - Date: 2012-06-03 10:52:44 Econometrics Statistical inference Regression analysis Maximum likelihood Parametric model Linear regression Consistent estimator Matrix norm Loss function Statistics Estimation theory Statistical theory
76	Nonparametric methods for directional data Eduardo García–Portugués (University of Copenhagen) Joint work with I. Van Keilegom, R. M. Crujeiras and W. González–Manteiga In this talk we will introduce two nonparame Add to Reading List Source URL: www.eco.uc3m.es Language: English - Date: 2015-04-08 06:50:09 Econometrics Regression analysis Statistical tests Resampling Estimator Nonparametric regression Linear regression Statistics Statistical inference Non-parametric statistics
77	IEEE SIGNAL PROCESSING LETTERS, VOL. 16, NO. 6, JUNEPREPRINT) Fast multidimensional entropy estimation by k-d partitioning Dan Stowell, Mark D. Plumbley Abstract—We describe a non-parametric estimator for the Add to Reading List Source URL: c4dm.eecs.qmul.ac.uk Language: English - Date: 2009-05-13 08:48:24 Statistical inference M-estimators Robust statistics Maximum likelihood Efficient estimator Estimator Median Consistent estimator Kernel density estimation Statistics Estimation theory Statistical theory
78	3. The Generalized Method of Moments The Generalized Method of Moments, as the name suggest, can be thought of just as a generalization of the classical MM. A key in the GMM is a set of population moment conditions that Add to Reading List Source URL: lipas.uwasa.fi Language: English - Date: 2009-11-16 04:15:50 Econometrics Generalized method of moments Linear least squares Linear regression Estimator Least squares Variance M-estimator Covariance Statistics Regression analysis Estimation theory
79	Chapter 1 Heuristics The official dogma on parametric estimation is: Good estimators converge to the right thing and have limiting normal distributions; moreover, the variance of the limiting distribution can’t be sma Add to Reading List Source URL: www.stat.yale.edu Language: English - Date: 2010-09-07 00:00:23 Consistent estimator Maximum likelihood Fisher information Fisher consistency Loss function Estimator Sufficient statistic Delta method M-estimator Statistics Estimation theory Statistical theory
80	Chapter 1 Rise of the Machines Larry Wasserman On the 50th anniversary of the Committee of Presidents of Statistical Societies I reflect on the rise of the field of Machine Learning and what it means Add to Reading List Source URL: www.stat.cmu.edu Language: English - Date: 2013-02-16 16:55:39 Machine learning Expectation–maximization algorithm Errors-in-variables models Estimator Kernel density estimation M-estimator Minimax estimator Statistics Estimation theory Maximum likelihood

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