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Maximum likelihood estimation
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#	Item
81	Journal of Applied Statistics, Vol. 28, No. 6, 2001, Dynamic paired comparison models with stochastic variances MARK E. GLICKMAN, Boston University, Boston, MA 02215, USA Add to Reading List Source URL: www.glicko.net Language: English - Date: 2009-12-24 15:06:38 Estimation theory Statistical theory Statistical models Regression analysis Probability distributions Stochastic volatility Normal distribution Generalized linear model Maximum likelihood estimation Prior probability Variance Autoregressive model
82	Deformable Template As Active Basis Ying Nian Wu, Zhangzhang Si, Chuck Fleming, and Song-Chun Zhu UCLA Department of Statistics http://www.stat.ucla.edu/∼ywu/ActiveBasis.html Abstract Add to Reading List Source URL: www.stat.ucla.edu Language: English - Date: 2007-08-20 02:10:20 Statistical theory Probability distributions Signal processing Timefrequency analysis Wavelet Regression analysis KullbackLeibler divergence FO Maximum likelihood estimation Exponential distribution Closed and exact differential forms Bayesian multivariate linear regression
83	Efficient Estimation of Integrated Volatility Incorporating Trading Information Yingying Li† Shangyu Xie‡ Add to Reading List Source URL: www.cb.cityu.edu.hk Language: English - Date: 2016-07-11 23:25:12 Estimation theory Statistical theory Maximum likelihood estimation Consistent estimator Fisher information Parametric model Efficient estimator Asymptotic theory Volatility Estimator
84	AUTOMATIC MUSIC TAGGING WITH TIME SERIES MODELS Luke Barrington Emanuele Coviello University of California, University of California, San Diego San Diego Add to Reading List Source URL: eceweb.ucsd.edu Language: English - Date: 2015-07-31 19:00:26 Estimation theory Statistical models Statistical theory Cluster analysis Machine learning Mixture model Expectationmaximization algorithm Maximum likelihood estimation
85	Selection of a suitable data set and model for the estimation of genetic parameters of the weaning weight in beef cattle* Add to Reading List Source URL: www.archanimbreed.com Language: English - Date: 2016-01-06 06:20:57 Genetics Heritability Genetic variance Genetic correlation Normal distribution Random effects model Restricted maximum likelihood Best linear unbiased prediction Variance Explained variation Genome-wide complex trait analysis
86	Estimating population size using the network scale up method Add to Reading List Source URL: www.stat.washington.edu Language: English - Date: 2016-07-01 11:51:28 Statistical theory Estimation theory Statistical inference Summary statistics Probability distributions Bias of an estimator Standard deviation Normal distribution Maximum likelihood estimation Random walk Estimator Sampling
87	This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOITKDE, IEEE Tr Add to Reading List Source URL: people.tubri.org Language: English - Date: 2015-03-18 18:22:04 Robust statistics Estimation theory Statistical theory Covariance and correlation M-estimators Outlier Maximum likelihood estimation Mixture model Expectationmaximization algorithm Sample mean and covariance Efficiency Normal distribution
88	Inference, Models and Simulation for Complex Systems Lecture 3 Prof. Aaron Clauset 1 Add to Reading List Source URL: tuvalu.santafe.edu Language: English - Date: 2011-09-22 11:32:56 Probability distributions Exponentials Infinitely divisible probability distributions Statistical models Actuarial science Exponential distribution Power law Maximum likelihood estimation Cumulative distribution function KolmogorovSmirnov test Heavy-tailed distribution
89	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
90	Which cliques? • In general, an undirected model can place potentials on any subset of the cliques of the graph. Lecture 11: Iterative Proportional Fitting Add to Reading List Source URL: www.cs.nyu.edu Language: English - Date: 2009-10-06 18:57:16 Statistical theory Estimation theory XC KullbackLeibler divergence Cross entropy Clique Maximum likelihood estimation

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