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Statistical theory
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#	Item
701	A NNALES DE L’I. H. P., SECTION B A MIR D EMBO Y UVAL P ERES JAY ROSEN O FER Z EITOUNI Add to Reading List Source URL: www.math.csi.cuny.edu Language: English - Date: 2009-05-03 17:58:27 Stochastic processes Fractals Dimension theory Metric geometry Statistical mechanics Brownian motion Hausdorff dimension Hitting time
702	UNIVERSITY OF OXFORD DEPARTMENT OF STATISTICS MSc AND POSTGRADUATE DIPLOMA IN APPLIED STATISTICS Add to Reading List Source URL: www.stats.ox.ac.uk Language: English - Date: 2015-10-05 05:41:34 Statistical inference Formal sciences Psychometrics Philosophy of science Statistical theory Statistics Thesis Data analysis Nonparametric statistics Statistical hypothesis testing Regression analysis Computational statistics
703	LEARNING HIDDEN VARIABLES IN PROBABILISTIC GRAPHICAL MODELS T HESIS SUBMITTED FOR THE DEGREE OF Add to Reading List Source URL: www.cs.huji.ac.il Language: English - Date: 2015-08-10 08:23:23 Statistical models Bayesian network Graphical model Nir Friedman Hidden variable theory Causality Expectationmaximization algorithm Expected value Latent variable
704	Bayesian alternatives to null-hypothesis significance testing for repeated-measures designs Add to Reading List Source URL: web.uvic.ca Language: English - Date: 2016-06-20 20:18:09 Statistical inference Hypothesis testing Design of experiments Statistical theory Bayesian statistics Statistical hypothesis testing Bayesian inference Analysis of variance Prior probability Bayes factor Bayes estimator Bayesian
705	UB Riskcenter Working Paper Series University of Barcelona Research Group on Risk in Insurance and Finance www.ub.edu/riskcenter Working paper \\ Number of pages 25 Add to Reading List Source URL: www.ub.edu Language: English - Date: 2014-04-12 05:48:25 Nonparametric statistics Estimation theory Robust statistics Statistical inference Actuarial science Kernel density estimation Variance Standard deviation L-estimator Skewness Expected value Value at risk
706	EFFICIENT MONTE CARLO OPTIMIZATION FOR MULTI-LABEL CLASSIFIER CHAINS Jesse Read, Luca Martino∗ David Luengo∗ Dept. of Signal Theory and Communications Add to Reading List Source URL: users.ics.aalto.fi Language: English - Date: 2013-03-13 05:58:27 Machine learning Statistical classification Classifier chains Multi-label classification Pattern recognition Support vector machine Probabilistic classification Supervised learning Maximum a posteriori estimation Naive Bayes classifier Structured support vector machine
707	From Sequences to Population Parameters: Using LAMARC for Data-Mining Lucian Smith, Mary Kuhner University of Washington, Department of Genome Sciences Poster available at: http://evolution.gs.washington.edu/lamarc/Tutor Add to Reading List Source URL: evolution.gs.washington.edu Language: English - Date: 2012-05-08 17:42:37 Statistical inference Genetics Statistical theory Microsatellite Population genetics Confidence interval Bayesian inference Coalescent theory
708	Context-Sensitive Induction Patrick Shafto1 , Charles Kemp1 , Elizabeth Baraff1 , John D. Coley2 , & Joshua B. Tenenbaum1 1 Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology 2 Add to Reading List Source URL: ccdlab.rutgers.edu Language: English - Date: 2015-03-24 11:58:24 Reasoning Inductive reasoning Philosophy of science Statistical inference Critical thinking Causality Concept learning Bayesian network Inference Bayesian inference Theory Argument
709	326 IEEE TRANSACTIONS ON IMAGE PROCESSING, VOL. 17, NO. 3, MARCH 2008 Parameter Estimation in TV Image Restoration Using Variational Distribution Approximation Add to Reading List Source URL: decsai.ugr.es Language: English - Date: 2008-02-28 03:58:00 Statistics Statistical theory Bayesian statistics Conjugate prior Hyperprior Normal distribution Bayesian inference Hyperparameter Bayesian network Prior probability Hidden Markov model Maximum likelihood estimation
710	2015 IEEE International Conference on Robotics and Automation (ICRA) Washington State Convention Center Seattle, Washington, May 26-30, 2015 Self-tuning M-estimators G. Agamennoni, P. Furgale and R. Siegwart Add to Reading List Source URL: europa2.informatik.uni-freiburg.de Language: English - Date: 2016-01-26 19:52:59 Estimation theory Statistical theory M-estimators Statistical inference Bayesian statistics Maximum likelihood estimation Normal distribution Bayes estimator Efficiency Estimator Marginal likelihood operator

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