Maximum likelihood - PDFSEARCH.IO - Document Search Engine

Maximum likelihood
Results: 2166

#	Item
261	STATISTICS Dalarna University D-level Master’s Thesis 2007 Which estimator of the dispersion parameter for the Gamma family Add to Reading List Source URL: www.statistics.du.se Language: English - Date: 2009-11-24 08:00:13 Statistical inference Maximum likelihood Estimator Normal distribution Bias of an estimator Gamma distribution Consistent estimator Generalized linear model Scale parameter Statistics Estimation theory Statistical theory
262	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
263	Some Determinants of Cost Efficiency in German Public Transport Matthias Walter∗ 22nd July 2009 Submission to the 11TH CONFERENCE ON COMPETITION AND OWNERSHIP IN LAND TRANSPORT Add to Reading List Source URL: ses.library.usyd.edu.au Language: English - Date: 2010-02-19 06:35:00 Regression analysis Stochastic frontier analysis Data envelopment analysis Macroeconomics Inefficiency Economic model Econometrics Macroeconomic model Maximum likelihood Economics Estimation theory Statistics
264	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
265	THIS IS A DRAFT VERSION. FINAL VERSION TO BE PUBLISHED AT NIPS ’06 Structure Learning in Markov Random Fields Sridevi Parise Bren School of Information and Computer Science Add to Reading List Source URL: www.ics.uci.edu Language: English - Date: 2006-09-04 17:32:02 Probability theory Estimation theory Graphical models Marginal likelihood Expectation–maximization algorithm Variational Bayesian methods Normal distribution Maximum likelihood Bayesian network Statistics Bayesian statistics Statistical theory
266	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
267	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
268	Evidence Estimation for Bayesian Partially Observed MRFs Yutian Chen Department of Computer Science University of California, Irvine Irvine, CA 92697 Add to Reading List Source URL: www.ics.uci.edu Language: English - Date: 2013-02-14 03:02:58 Normal distribution Expectation–maximization algorithm Variational Bayesian methods Bayesian network Markov chain Monte Carlo Maximum likelihood Deviance information criterion Pierre-Simon Laplace Markov random field Statistics Bayesian statistics Marginal likelihood
269	Bayesian Posterior Sampling via Stochastic Gradient Fisher Scoring Sungjin Ahn Dept. of Computer Science, UC Irvine, Irvine, CA, USA SUNGJIA @ ICS . UCI . EDU Add to Reading List Source URL: www.ics.uci.edu Language: English - Date: 2012-05-22 12:55:14 Fisher information Markov chain Monte Carlo Normal distribution Stochastic gradient descent Maximum a posteriori estimation Confidence interval Central limit theorem Score Expectation–maximization algorithm Statistics Estimation theory Maximum likelihood
270	Measuring Bias and Uncertainty in DW-NOMINATE Ideal Point Estimates via the Parametric Bootstrap Preliminary Draft, please do not cite without permission Royce Carroll Add to Reading List Source URL: www.voteview.com Language: English - Date: 2013-11-20 15:56:09 Estimation theory Data analysis NOMINATE Bootstrapping Logistic regression Normal distribution Maximum likelihood Parameter Exponential distribution Statistics Statistical inference Statistical theory

UPDATE