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Likelihood function
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111	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
112	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
113	ESTIMATION OF UNNORMALIZED STATISTICAL MODELS WITHOUT NUMERICAL INTEGRATION Michael U. Gutmann1,3 and Aapo Hyv¨arinen1,2,3 1 Add to Reading List Source URL: www.me.inf.kyushu-u.ac.jp Language: English - Date: 2013-08-15 22:08:43 Maximum likelihood Parametric model Likelihood function Exponential family Consistent estimator Score Fisher information Extremum estimator Estimation theory Statistics Statistical theory
114	Deterministic Latent Variable Models and their Pitfalls Max Welling∗ Chaitanya Chemudugunta Nathan Sutter Bren School of Information and Computer Science University of California, Irvine Add to Reading List Source URL: www.ics.uci.edu Language: English - Date: 2008-04-16 00:56:41 Information theory Statistical natural language processing Categorical data Probabilistic latent semantic analysis Expectation–maximization algorithm Perplexity Entropy Kullback–Leibler divergence Likelihood function Statistics Estimation theory Statistical theory
115	Bayesian decision theory as a model of human visual perception: Testing Bayesian transfer Add to Reading List Source URL: psych.nyu.edu Language: English - Date: 2009-03-25 11:25:00 Statistical theory Bayesian inference Likelihood principle Prior probability Loss function Likelihood function Bayes estimator Statistics Bayesian statistics Estimation theory
116	arXiv:1401.2838v1 [cs.LG] 13 JanGPS-ABC: Gaussian Process Surrogate Approximate Bayesian Computation Max Welling Add to Reading List Source URL: www.ics.uci.edu Language: English - Date: 2014-04-19 07:04:55 Statistical inference Econometrics Confidence interval Measurement Marginal likelihood Likelihood function Normal distribution Markov chain Maximum likelihood Statistics Estimation theory Bayesian statistics
117	Estimation of affine term structure models with spanned or unspanned stochastic volatility Add to Reading List Source URL: faculty.chicagobooth.edu Language: English - Date: 2015-01-12 11:52:18 Mathematical finance Bayesian statistics Maximum likelihood Expectation–maximization algorithm Likelihood-ratio test Stochastic volatility Autoregressive conditional heteroskedasticity Likelihood function Statistics Estimation theory Statistical theory
118	MASTER THESIS IN MICRODATA ANALYSIS Modelling S shaped hazard function A case of evaluating Volvo Cars training project Author: Add to Reading List Source URL: www.statistics.du.se Language: English - Date: 2014-06-25 03:06:38 Rectangular function Mathematics Survival analysis Statistical models M-estimators Estimation theory Statistics Likelihood function
119	Exploiting Inference for Approximate Parameter Learning in Discriminative Fields: An Empirical Study Sanjiv Kumar, Jonas August, 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 18:50:53 Graphical models Bayesian statistics Probability theory Maximum likelihood Likelihood function Conditional random field Belief propagation Statistics Estimation theory M-estimators
120	The Randomness of the Real World In the real-world, there are many random (formally, stochastic) systems changing over time which can be modelled very accurately through sequences of dependent random variables than indep Add to Reading List Source URL: eagle-essays.com Language: English - Date: 2015-03-10 11:24:21 Stochastic processes Estimation theory Markov chain Random walk Bioinformatics Stochastic matrix Andrey Markov Maximum likelihood Likelihood function Statistics Markov models Markov processes

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