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Likelihood function
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61	Learning stable, regularised latent models of neural population dynamics Lars Buesing, Jakob H. Macke and Maneesh Sahani Gatsby Computational Neuroscience Unit University College London, UK 17 Queen Square, London, WC1N Add to Reading List Source URL: www.mackelab.org Language: English - Date: 2016-08-04 15:02:44 Estimation theory Regression analysis Statistical models Bayesian statistics Econometrics Maximum likelihood estimation Expectationmaximization algorithm Variational Bayesian methods Linear regression Autoregressive model Variance function Mixture model
62	Learning Discriminative Fisher Kernels Laurens van der Maaten Pattern Recognition & Bio-informatics Laboratory, Delft University of Technology, THE NETHERLANDS Add to Reading List Source URL: lvdmaaten.github.io Language: English - Date: 2016-07-16 15:30:43 Estimation theory Machine learning Statistical classification Fisher kernel Categorical data Pattern recognition Kernel method Positive-definite kernel Support vector machine Maximum likelihood estimation Kernel Likelihood function
63	Policy Gradient Coagent Networks Philip S. Thomas Department of Computer Science University of Massachusetts Amherst Amherst, MA 01002 Add to Reading List Source URL: psthomas.com Language: English - Date: 2013-11-16 15:49:43 Estimation theory Reinforcement learning Fisher information Likelihood function
64	p-values: The insight to modern statistical inference D A S Fraser ∗ Add to Reading List Source URL: errorstatistics.files.wordpress.com Language: English - Date: 2016-06-28 14:43:14 Estimation theory Statistical theory Econometrics Bayesian statistics Statistical inference Likelihood function Confidence interval Sufficient statistic Bias of an estimator Observed information Maximum likelihood estimation Likelihood principle
65	Bulletin of the Seismological Society of America, Vol. 97, No. 6, pp. 1890–1910, December 2007, doi: Real-Time Estimation of Fault Rupture Extent Using Near-Source versus Far-Source Classification b Add to Reading List Source URL: www.eqh.dpri.kyoto-u.ac.jp Language: English - Date: 2009-05-21 20:56:26 Statistical classification Multivariate statistics Estimation theory Probability distributions Bayesian statistics Linear discriminant analysis Discriminant function analysis Seismometer Normal distribution Likelihood function Mode Earthquake
66	c 2009 Society for Industrial and Applied Mathematics ! SIAM REVIEW Vol. 51, No. 4, pp. 661–703 Add to Reading List Source URL: tuvalu.santafe.edu Language: English - Date: 2010-10-13 18:48:29 Probability distributions Estimation theory Statistical models Exponentials Actuarial science Maximum likelihood estimation Power law Cumulative distribution function KolmogorovSmirnov test Likelihood function Expected value Mode
67	Energetic Natural Gradient Descent Add to Reading List Source URL: psthomas.com Language: English - Date: 2016-05-26 17:40:03 Estimation theory Statistical theory Parametric model Loss function Fisher information Expectationmaximization algorithm Divergence Likelihood function Gradient descent
68	16 Basic Bayesian Methods Mark E. Glickman and David A. van Dyk Summary In this chapter, we introduce the basics of Bayesian data analysis. The key ingredients to a Add to Reading List Source URL: www.glicko.net Language: English - Date: 2009-12-24 15:06:45 Bayesian statistics Bayesian inference Prior probability Beta distribution Likelihood function Statistical inference Normal distribution Confidence interval Posterior probability Conjugate prior Marginal likelihood
69	Errata Introduction to Probability, 2nd Edition Dimitri P. Bertsekas and John N. Tsitsiklis Athena Scientific, 2008 (last updated) • p. 79, line −2: Change “Polish” to “Prussian” Add to Reading List Source URL: athenasc.com Language: English - Date: 2015-12-09 00:03:20 Statistics Statistical theory Estimation theory Probability distributions Bayesian statistics Confidence interval Measurement Quantitative marketing research Likelihood function Normal distribution Gamma distribution Generalised Hough transform
70	Competing process hazard function models for player ratings in ice hockey Add to Reading List Source URL: www-stat.wharton.upenn.edu Language: English - Date: 2013-10-03 09:38:03 Statistics Statistical theory Statistical models Probability distributions Estimation theory Regression analysis Normal distribution Bayesian network Maximum likelihood estimation Linear regression Conjugate prior Parameter

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