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Probability and statistics
Results: 5057

#	Item
991	Strong laws of large numbers for capacities ∗ Zengjing Chen Shandong University and Ajou University JinanChina, Suwon Korea E-mail: Add to Reading List Source URL: www.statistics.gov.hk Language: English - Date: 2013-08-22 04:39:21 Probability and statistics Choquet integral Central limit theorem Expected value Almost surely Random variable Brownian motion Ordinal number Markov chain Statistics Probability theory Mathematical analysis
992	Conditional Random Fields: An Introduction∗ Hanna M. Wallach February 24, 2004 1 Add to Reading List Source URL: www.inference.phy.cam.ac.uk Language: English - Date: 2004-09-21 19:00:07 Probability theory Statistical theory Graphical models Bayesian statistics Machine learning Conditional random field Hidden Markov model Markov random field Information theory Statistics Probability and statistics Probability
993	Phase type distributions for competing risks Bo Henry Lindqvist* Norwegian University of Science and Technology, Trondheim, Norway Phase-type distributions represent the time to absorption for a finite st Add to Reading List Source URL: www.statistics.gov.hk Language: English - Date: 2013-08-22 04:39:21 Markov chain Phase-type distribution Expectation–maximization algorithm Estimation theory Stochastic matrix Monte Carlo method Discrete phase-type distribution Statistics Markov models Probability and statistics
994	Still searching for principles: a response to Goodman et al. We appreciate Goodman et al’s efforts to address concerns raised in Marcus and Davis (2013), but we remain unconvinced. Multiple models To refresh the reade Add to Reading List Source URL: www.cs.nyu.edu Language: English - Date: 2015-04-21 10:34:40 Bayesian statistics Philosophy of science Concept learning Learning theory Machine learning Bayesian inference Statistical inference Bayesian probability Tannenbaum Statistics Science Statistical theory
995	Information Theory in Ten Minutes Spencer Tipping November 25, 2013 Disclaimer: I’m not an academic, nor have I taken any classes on information theory. I’m a dropout and Wikipedia student who uses it in potentially Add to Reading List Source URL: spencertipping.com Language: English - Date: 2013-11-25 23:40:47 Probability theory Inductive reasoning Measurement Entropy Statistical theory Random variable Probability space Coin flipping Lossless data compression Randomness Probability and statistics Information theory
996	3.0 METHODOLOGY 3.1 SPI Defined McKee et aldeveloped the Standardized Precipitation Index (SPI) for the purpose of defining and monitoring drought. Among others, the Colorado Climate Center, the Western Regional Add to Reading List Source URL: climate.atmos.colostate.edu Language: English - Date: 2005-08-10 15:34:35 Normal distribution Gamma distribution Scale parameter Probability distribution Skewness Survival analysis Exponential distribution Pareto distribution Statistics Mathematical analysis Probability and statistics
997	mar253_20_20208.qxd:27 AM Add to Reading List Source URL: www.bm.ust.hk Language: English - Date: 2010-10-13 00:38:24 Probability and statistics Political philosophy Scheduling algorithms Operations research FIFO The Queue Queueing theory Queueing model Queue Statistics Markov models Stochastic processes
998	Moyal Lecture : 3 Nov., 2006 Markov Chains as Models in Statistical Mechanics. Eugene Seneta Add to Reading List Source URL: maths.mq.edu.au Language: English - Date: 2014-08-14 21:51:46 Probability and statistics Markov chain Ehrenfest model Markov property Stochastic matrix Entropy Urn problem Random walk Ludwig Boltzmann Statistics Markov models Markov processes
999	HERD: The Highest Expected Reward Decoding for HMMs with Application to Recombination Detection ˇ Brejová Brona Department of Computer Science Add to Reading List Source URL: www.cs.ucr.edu Language: English - Date: 2010-08-20 17:45:42 Statistics Viterbi algorithm Probability and statistics Hidden Markov model Forward–backward algorithm Pointwise Mathematics Annotation Markov models Error detection and correction Dynamic programming
1000	Judgment under Uncertainty: Heuristics and Biases Amos Tversky; Daniel Kahneman Science, New Series, Vol. 185, NoSep. 27, 1974), ppStable URL: http://links.jstor.org/sici?sici=%%2 Add to Reading List Source URL: people.hss.caltech.edu Language: English - Date: 2007-04-09 18:12:18 Probability theory Probability and statistics Bayesian statistics Heuristics Representativeness heuristic Probability interpretations Odds Cognitive bias Prior probability Statistics Probability Science