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M-estimator
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#	Item
211	Sample Complexity of Composite Likelihood Joseph K. Bradley Carlos Guestrin Carnegie Mellon University Add to Reading List Source URL: www.select.cs.cmu.edu Language: English - Date: 2012-04-11 16:43:47 Statistical inference M-estimators Maximum likelihood Econometrics Efficient estimator Estimator Likelihood function Loss function Normal distribution Statistics Estimation theory Statistical theory
212	Rose, Smith: Symbolic Maximum Likelihood Estimation with Mathematica Sonderforschungsbereich 386, Paper[removed]Online unter: http://epub.ub.uni-muenchen.de/ Add to Reading List Source URL: epub.ub.uni-muenchen.de Language: English - Date: 2012-05-22 04:44:21 M-estimators Statistical theory Maximum likelihood Estimator Estimation theory Statistics Statistical inference
213	Robust Locally Weighted Regression and Smoothing Scatterplots Author(s): William S. Cleveland Reviewed work(s): Source: Journal of the American Statistical Association, Vol. 74, No[removed]Dec., 1979), pp[removed]Published Add to Reading List Source URL: synapse.princeton.edu Language: English - Date: 2012-08-08 13:39:15 Econometrics Estimation theory Robust regression Local regression M-estimator Linear regression Statistics Regression analysis Robust statistics
214	Chapter 16 Simulation You will recall from your previous statistics courses that quantifying uncertainty in statistical inference requires us to get at the sampling distributions of things like estimators. When the very Add to Reading List Source URL: www.stat.cmu.edu Language: English - Date: 2012-03-21 11:27:00 Monte Carlo methods Non-uniform random numbers Normal distribution Quantile function Cumulative distribution function Exponential distribution M-estimator Random number generation Rejection sampling Statistics Probability and statistics Mathematical analysis
215	Robust Kalman filter and smoother for errors-in-variables model with observation outliers based on Least-Trimmed-Squares Jaafar ALMutawa Department of Mathematics and Statistics, King Fahd University of Petroleum and Min Add to Reading List Source URL: eprints.kfupm.edu.sa Language: English - Date: 2011-04-06 01:40:43 Robot control Estimation theory Kalman filter Errors-in-variables models Filter Holomorphic functional calculus M-estimator Statistics Control theory Stochastic differential equations
216	OPERATIONS RESEARCH Vol. 60, No. 4, July–August 2012, pp. 739–756 ISSN 0030-364X (print) ISSN[removed]online) http://dx.doi.org[removed]opre[removed] © 2012 INFORMS Add to Reading List Source URL: www.ise.ufl.edu Language: English - Date: 2013-06-15 17:51:05 Statistical inference Regression analysis Parametric statistics Estimator Linear regression M-estimator Robust statistics Quantile regression Normal distribution Statistics Estimation theory Statistical theory
217	Efficient Estimation of Average Treatment Effects Using the Estimated Propensity Score Add to Reading List Source URL: scholar.harvard.edu Language: English - Date: 2015-01-30 06:12:42 Regression analysis M-estimators Statistical theory Propensity score Expected value Linear regression Efficient estimator Generalized method of moments Instrumental variable Statistics Estimation theory Econometrics
218	idescat. SORT. Locally adaptive density estimation on Riemannian manifolds. Volume 37 (2) Add to Reading List Source URL: www.idescat.cat Language: English - Date: 2013-12-30 06:43:39 M-estimators Statistical theory Non-parametric statistics Riemannian manifold Kernel density estimation Estimator Differentiable manifold Sectional curvature Normal distribution Statistics Estimation theory Statistical inference
219	NISS On the asymptotic normality and variance estimation for nondifferentiable survey estimators Jianqiang C. Wang and J.D. Opsomer Add to Reading List Source URL: www.niss.org Language: English - Date: 2010-11-29 14:23:54 Statistical inference Robust statistics Estimator Bias of an estimator Normal distribution Median Variance Efficient estimator M-estimator Statistics Estimation theory Statistical theory
220	Combining Spatial and Telemetric Features for Learning Animal Movement Models Berk Kapicioglu Robert E. Schapire Princeton University Add to Reading List Source URL: www.berkkapicioglu.com Language: English - Date: 2013-11-30 21:06:02 Maximum likelihood Stochastic optimization M-estimator Statistics Estimation theory Expectation–maximization algorithm

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