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Maximum likelihood
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#	Item
741	Statistics 582, Midterm Exam Solutions Wellner; [removed]points) Define any three of the following terms. In each case, provide an appropriate context for your definition. (a) An inadmissible decision rule. Add to Reading List Source URL: www.stat.washington.edu Language: English - Date: 2015-02-14 19:25:43 Bayes estimator Parametric model Maximum likelihood Loss function Sufficient statistic Bias of an estimator Symbol Statistics Statistical theory Estimation theory
742	Statistics 582, Problem Set 2 Solutions Wellner; [removed]Consider nonparametric maximum likelihood estimation of F in the right-censored data problem considered in class, but extend the argument to include ties as f Add to Reading List Source URL: www.stat.washington.edu Language: English - Date: 2015-01-21 18:17:12 Maximum likelihood Science Philosophy of science Theorems and definitions in linear algebra Fisher consistency Estimation theory Statistical theory M-estimators
743	Statistics 582, Problem Set 1 Solutions Wellner; [removed]Lehmann and Casella, TPE, Problem 4.9, page 504. Solution: (a) The density of a bivariate normal random vector (X, Y ) with µ1 = µ2 = 0, variances σ12 ≡ Add to Reading List Source URL: www.stat.washington.edu Language: English - Date: 2015-01-15 11:29:59 Expectation–maximization algorithm Missing data Multivariate normal distribution Maximum likelihood Symbol Orbifold Statistics Estimation theory Normal distribution
744	This discussion paper is/has been under review for the journal Natural Hazards and Earth System Sciences (NHESS). Please refer to the corresponding final paper in NHESS if available. Discussion Paper Nat. Hazards Earth Add to Reading List Source URL: www.nat-hazards-earth-syst-sci-discuss.net Language: English - Date: 2015-03-31 12:34:33 Bayesian statistics Design of experiments Statistical inference Likelihood function Maximum likelihood Statistical hypothesis testing Uniform distribution Poisson distribution Likelihood principle Statistics Estimation theory Statistical theory
745	The Hobbs Weed Infestation Problem John C. Nash, Telfer School of Management, University of Ottawa, Ottawa, Canada Anders Nielsen, Technical University of Denmark, Charlottenlund, Denmark Ben Bolker, McMaster University, Add to Reading List Source URL: groups.nceas.ucsb.edu Language: English - Date: 2012-09-21 18:43:40 Mathematical optimization Least squares Applied mathematics M-estimators ADMB Free statistical software BFGS method Non-linear least squares Maximum likelihood Statistics Regression analysis Numerical analysis
746	Supporting User-Defined Functions on Uncertain Data Thanh T. L. Tran† , Yanlei Diao† , Charles Sutton‡ , Anna Liu† † University of Massachusetts, Amherst Add to Reading List Source URL: www.vldb.org Language: English - Date: 2013-06-29 06:27:43 Estimation theory Functions and mappings Data analysis Bayesian statistics Normal distribution Maximum likelihood Variance Multivariate normal distribution Likelihood function Statistics Mathematics Mathematical analysis
747	arXiv:1111.5479v2 [stat.ML] 7 Aug[removed]The Graphical Lasso: New Insights and Alternatives Rahul Mazumder∗ Trevor Hastie† Department of Statistics Add to Reading List Source URL: arxiv.org Language: English - Date: 2012-08-08 20:21:37 Estimation theory Statistical theory Maximum likelihood Eigenvalues and eigenvectors Matrix Linear least squares Algebra Linear algebra Mathematics
748	17 MDL in Context In this chapter, we compare refined MDL to various other statistical inference methods. We start in Section 17.1, with a comparison between MDL and various frequentist approaches. Section 17.2 consider Add to Reading List Source URL: homepages.cwi.nl Language: English - Date: 2007-08-24 08:53:49 Estimation theory Statistical inference Frequentist inference Likelihood principle Bayesian inference Minimum message length Admissible decision rule Bayes estimator Principle of maximum entropy Statistics Statistical theory Bayesian statistics
749	1 Chapter 3 Lower Bounds for Estimation 1. Introduction and Examples 2. Cram´ Add to Reading List Source URL: www.stat.washington.edu Language: English - Date: 2007-03-06 20:02:20 Parametric model Bias of an estimator Law of large numbers Maximum likelihood Hájek–Le Cam convolution theorem Statistics Statistical theory Estimation theory
750	Journal of Machine Learning Research[removed]Submitted 3/13; Published[removed]Communication-Efficient Algorithms for Statistical Optimization Add to Reading List Source URL: arxiv.org Language: English - Date: 2013-10-13 22:21:29 Fisher information Loss function Bias of an estimator Maximum likelihood Fisher consistency Statistics Statistical theory Estimation theory

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