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Expectation
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#	Item
601	Combining Predictive Distributions Tilmann Gneiting, University of Heidelberg Heidelberg, Germany Roopesh Ranjan, GE Research, Bangalore, India arXiv:1106.1638v1 [math.ST] 8 Jun 2011 Add to Reading List Source URL: arxiv.org Language: English - Date: 2011-06-08 20:13:51 Normal distribution Cumulative distribution function Random variable Conditional expectation Prediction interval Independence Multivariate normal distribution Variance Probability space Statistics Probability theory Probability and statistics
602	Latent Class Analysis Jeroen K. Vermunt & Jay Magidson The basic idea underlying latent class (LC) analysis is a very simple one: some of the parameters of a postulated statistical model differ across unobserved subgroup Add to Reading List Source URL: statisticalinnovations.com Language: English - Date: 2006-09-05 12:11:48 Econometrics Categorical data Multivariate statistics Latent class model Expectation–maximization algorithm Latent variable model Structural equation modeling Logistic regression Mixture model Statistics Regression analysis Statistical models
603	MACQUARIE UNIVERSITY STATISTICS DEPARTMENT SEMINAR Speaker: A/Prof Xinyuan Song, Department of Statistics, Chinese University of Hong Kong Date: Tuesday 28 April 2015, Time 2pm Venue: E4A523 Title: Statistics analysis of Add to Reading List Source URL: stat.mq.edu.au Language: English - Date: 2015-04-19 22:05:02 Bioinformatics Hidden Markov model Expectation–maximization algorithm Latent variable Estimation theory Book:Machine Learning - The Complete Guide Statistics Statistical models Markov models
604	An Introduction to Probability Models for Marketing Research Peter S. Fader University of Pennsylvania Bruce G. S. Hardie Add to Reading List Source URL: www.brucehardie.com Language: English - Date: 2013-07-16 16:45:35 M-estimators Bayesian statistics Maximum likelihood Likelihood function Statistical models Expectation–maximization algorithm Statistics Estimation theory Statistical theory
605	PDF Document Add to Reading List Source URL: hrl.informatik.uni-freiburg.de Language: English - Date: 2003-12-15 05:10:20 Robot control Linear filters Bioinformatics Hidden Markov model Expectation–maximization algorithm Markov chain Robotics Kalman filter 3D scanner Statistics Estimation theory Markov models
606	Learning Motion Patterns of People for Compliant Robot Motion Maren Bennewitz† Grzegorz Cielniak‡ † Add to Reading List Source URL: hrl.informatik.uni-freiburg.de Language: English - Date: 2004-03-30 10:22:04 Likelihood function 3D scanner Dimensional analysis Statistics Estimation theory Expectation–maximization algorithm
607	(SAcLJ Substantive Legitimate Expectation in Singapore Administrative Law 237 Add to Reading List Source URL: www.sal.org.sg Language: English - Date: 2014-04-02 01:10:03 English administrative law Legitimate expectation in Singapore law Legitimate expectation Administrative law in Singapore R (Bancoult) v Secretary of State for Foreign and Commonwealth Affairs Natural justice Legal certainty Estoppel High Court of Singapore Law Common law Equity
608	Internships have become a prominent feature of the UK jobs landscape. For many professional careers there is now an expectation that graduates will go through an internship (or even several Add to Reading List Source URL: www.suttontrust.com Language: English - Date: 2014-11-11 11:35:18 Medical education in the United States Employment Internships National Minimum Wage Act Minimum wage Residency Interns Anonymous Education Learning Medical education
609	Multiple Imputation of Missing Values in Economic Surveys: Comparison of Competing Algorithms Masayoshi Takahashi1,2 and Takayuki Ito1 National Statistics Center, Tokyo, JAPAN 2 Corresponding author: Masayoshi Takahashi, Add to Reading List Source URL: www.statistics.gov.hk Language: English - Date: 2013-08-22 04:39:17 Statistical inference Monte Carlo methods Computational statistics Imputation SPSS Resampling Bootstrapping Expectation–maximization algorithm SAS Statistics Data analysis Missing data
610	GRAMMAR INDUCTION AND PARSING WITH DEPENDENCY-AND-BOUNDARY MODELS A DISSERTATION SUBMITTED TO THE DEPARTMENT OF COMPUTER SCIENCE AND THE COMMITTEE ON GRADUATE STUDIES Add to Reading List Source URL: nlp.stanford.edu Language: English - Date: 2013-12-13 22:01:08 Natural language processing Corpus linguistics Speech recognition Markov models Expectation–maximization algorithm Algorithm Lateen Part-of-speech tagging Mathematical optimization Linguistics Computational linguistics Science

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