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Maximum likelihood estimation
Results: 1796

#	Item
191	Bayesian Flexible Distribution Approach to Measuring the Economic Benefits of Sport-Fishing on Gran Canaria Using Contingent Valuation Add to Reading List Source URL: www.eafe-fish.org Language: English - Date: 2011-03-15 21:59:18 Statistical theory Statistical inference Bayesian inference Statistical forecasting Gibbs sampling Normal distribution Maximum likelihood Likelihood function Statistics Bayesian statistics Estimation theory
192	Parametric Herding Yutian Chen Max Welling Bren School of Information and Computer Science University of California, Irvine Add to Reading List Source URL: www.ics.uci.edu Language: English - Date: 2010-03-16 13:28:39 Machine learning Econometrics M-estimators Regression analysis Mixture model Maximum likelihood Boltzmann machine Expectation–maximization algorithm Vector quantization Statistics Estimation theory Statistical theory
193	Optimizing Neural Networks with Kronecker-factored Approximate Curvature James Martens Roger Grosse Department of Computer Science, University of Toronto Add to Reading List Source URL: www.cs.toronto.edu Language: English - Date: 2015-06-03 15:15:50 Estimation theory Neural networks Matrices Computational neuroscience Differential calculus Fisher information Maximum likelihood Gradient Linear map Mathematics Mathematical analysis Calculus
194	A Lazy Man’s Approach to Benchmarking: Semisupervised Classifier Evaluation and Recalibration Peter Welinder‡ Add to Reading List Source URL: www.ics.uci.edu Language: English - Date: 2013-04-11 10:56:51 Estimation theory Statistical classification Statistical inference Maximum likelihood Confidence interval Receiver operating characteristic Conjugate prior Gamma distribution Supervised learning Statistics Machine learning Biostatistics
195	Efficient Gradient-Based Inference through Transformations between Bayes Nets and Neural Nets Diederik P. Kingma Max Welling Machine Learning Group, University of Amsterdam Add to Reading List Source URL: www.ics.uci.edu Language: English - Date: 2014-05-14 15:18:52 Statistical models Statistical theory Statistical inference Expectation–maximization algorithm Bayesian network Gibbs sampling Normal distribution Maximum likelihood Latent variable Statistics Bayesian statistics Estimation theory
196	Measuring Convergence using Dynamic Equilibrium Models: Evidence from Chinese Provinces∗ Lei Pan(a) , Olaf Posch(b,c) and Michel van der Wel(c,d) (a) Wageningen University (b) Aarhus University, (c) CREATES, (d) Add to Reading List Source URL: www.oposch.com Language: English - Date: 2012-05-30 13:00:12 Economic growth Neoclassical growth model Estimation theory Maximum likelihood Convergence Series Statistics Macroeconomics Economics Statistical theory
197	Approximate Parameter Learning in Discriminative Fields Sanjiv Kumar and Martial Hebert The Robotics Institute Carnegie Mellon University Pittsburgh, PA 15213 Add to Reading List Source URL: www.sanjivk.com Language: English - Date: 2010-06-01 18:50:54 M-estimators Econometrics Bayesian statistics Maximum likelihood Likelihood function Loss function Statistics Estimation theory Statistical theory
198	Bayesian K-Means as a “Maximization-Expectation” Algorithm October 18, 2007 Abstract Add to Reading List Source URL: www.ics.uci.edu Language: English - Date: 2007-10-18 14:00:50 Statistical theory Expectation–maximization algorithm Missing data Statistical models Maximum likelihood Fisher information Variational Bayesian methods Marginal likelihood Mixture model Statistics Estimation theory Bayesian statistics
199	Continuous Time Stochastic Modeling in R User’s Guide and Reference Manual CTSM-R Development Team CTSM-R Version 1.0.0 Add to Reading List Source URL: ctsm.info Language: English - Date: 2015-04-17 10:25:27 Markov models Maximum likelihood Scientific modelling Likelihood function R Kalman filter Akaike information criterion Statistics Estimation theory Statistical theory
200	1792 • The Journal of Neuroscience, January 28, 2015 • 35(4):1792–1805 Behavioral/Cognitive Neural Mechanisms for Integrating Prior Knowledge and Likelihood in Value-Based Probabilistic Inference Add to Reading List Source URL: psych.nyu.edu Language: English - Date: 2015-02-23 11:10:34 Bayesian statistics Statistical inference Model selection Likelihood function Bootstrapping Prior probability Bayesian information criterion Maximum a posteriori estimation Statistical power Statistics Estimation theory Bayesian inference

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