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Probability theory
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#	Item
331	Powerpoint-presentation Information and Computing Sciences Add to Reading List Source URL: www.usefulpatterns.org Language: English - Date: 2015-04-25 08:23:03 Algorithmic information theory Computability theory Randomness Theoretical computer science Turing machine Kolmogorov complexity Algorithmically random sequence Algorithmic probability Minimum description length Complexity Ray Solomonoff Algorithm
332	Incorporating MR, ER and Robustness in Mean Variance Portfolio Choice F. Cavadini, A. Sbuelz, F. Trojani ECAS Course, Lugano, October 7-13, 2001 Add to Reading List Source URL: www.istfin.eco.usi.ch Language: English - Date: 2009-01-27 08:17:17 Estimation theory Statistical inference Statistical theory Bayesian statistics Decision theory Robust statistics L-estimator Expected utility hypothesis Estimator Prior probability Bayes estimator Frequentist inference
333	equ-lrn-smp-con-sfb-dp221105.dvi Add to Reading List Source URL: www.wiwi.uni-bonn.de Language: English - Date: 2008-10-06 05:48:06 Graph theory Markov chain Probability space
334	Testing for Regime Switching: A Comment Andrew V. Carter Department of Statistics University of California, Santa Barbara Douglas G. Steigerwald Department of Economics Add to Reading List Source URL: econ.ucsb.edu Language: English - Date: 2011-05-05 14:06:12 Probability distributions Estimation theory Maximum likelihood estimation Statistical theory Normal distribution
335	Lexicographic Beliefs and Assumption∗ Eddie Dekel† Amanda Friedenberg‡ Marciano Siniscalchi§ Add to Reading List Source URL: www.public.asu.edu Language: English - Date: 2016-05-09 14:51:10 Measure theory Probability theory Boolean algebra Sigma-algebra Measure Determinacy Model theory
336	Auxiliary Gibbs Sampling for Inference in Piecewise-Constant Conditional Intensity Models Zhen Qin University of California, Riverside Add to Reading List Source URL: rlair.cs.ucr.edu Language: English - Date: 2015-05-14 15:51:40 Markov processes Graph theory Markov chain Gibbs sampling Probability distribution Bayesian network Resampling Sampling
337	Stats workshop I Learning objectives: explain when and why statistics are necessary identify the information gained from the mean, standard error (SE), and standard error of the mean (SEM) understand the idea of random Add to Reading List Source URL: datanuggets.org Language: English - Date: 2014-03-06 18:44:41 Measurement Probability distributions Statistical theory Statistical inference Normal distribution Standard error Standard deviation Histogram Statistics Errors and residuals Deviation Sample size determination
338	CrossMark_Color_Stacked_p Add to Reading List Source URL: www.mackelab.org Language: English - Date: 2016-08-04 15:02:45 Bayesian statistics Probability distributions Statistical inference Statistical theory Psychometrics Overdispersion Beta-binomial distribution Beta distribution Bayesian inference Generalized linear model Prior probability Psychometric function
339	How biased are maximum entropy models? Jakob H. Macke Gatsby Computational Neuroscience Unit University College London, UK Add to Reading List Source URL: www.mackelab.org Language: English - Date: 2016-08-04 15:02:45 Statistical theory Information theory Randomness Statistical randomness Estimation theory Entropy Principle of maximum entropy KullbackLeibler divergence Maximum likelihood estimation Normal distribution Differential entropy Maximum entropy probability distribution
340	Appendix Clarification of Linear Grope Height Raising M. Freedman and P. Teichner Slava Krushkal and Frank Quinn recently brought to our attention misstatements in the proof of our linear grope height raising procedure w Add to Reading List Source URL: people.mpim-bonn.mpg.de Language: English - Date: 2012-08-01 06:52:27 Capped grope Measure theory Probability theory

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