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Conditional probability
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301	Package ‘discreteRV’ July 28, 2014 Maintainer Eric Hare Author Andreas Buja Version 1.1.2 License GPL-3 Add to Reading List Source URL: cran.r-project.org Language: English - Date: 2014-07-28 08:42:44 Probability Random variable Probability mass function Probability distribution Expected value Multivariate random variable Odds Marginal distribution Conditional probability Probability theory Statistics Probability and statistics
302	Curve Sampling and Geometric Conditional Simulation by Ayres C. Fan B.S., Electrical Engineering University of Minnesota, 2000 S.M., Electrical Engineering and Computer Science Add to Reading List Source URL: ssg.mit.edu Language: English - Date: 2012-02-01 13:34:49 Applied mathematics Monte Carlo methods Markov chain Monte Carlo Theoretical computer science Computational statistics Markov chain Metropolis–Hastings algorithm Gibbs sampling Segmentation Statistics Probability and statistics Markov models
303	North Dakota Standards Perceived as Challenging The standards listed in this file were identified by North Dakota teachers as those likely to present a challenge to teaching and learning at this grade level. As such, it Add to Reading List Source URL: ndcurriculuminitiative.org Language: English - Date: 2012-10-08 15:06:17 Mathematical analysis Normal distribution Probability distribution Mode Independence Irrational number Event Conditional probability Mean Probability theory Statistics Probability and statistics
304	Geometry: North Dakota Standards Perceived as Challenging The standards listed in this file were identified by North Dakota teachers as those likely to present a challenge to teaching and learning at this grade level. As Add to Reading List Source URL: ndcurriculuminitiative.org Language: English - Date: 2012-10-08 16:53:37 Measurement Conditional probability Event Independence Probability theory Probability Philosophical logic
305	Unit 1 Rigid motion: any transformation that preserves shape such as rotations, translations reflections, shifts and slides. If a figure is dilated or compressed the motion is no longer a rigid motion. Examples: on t Add to Reading List Source URL: www.mdk12.org Language: English - Date: 2012-08-16 15:09:22 Quadrilaterals Parabola Focus Area Circle Conditional probability Square Rectangle Method of exhaustion Geometry Conic sections Curves
306	Factored Conditional Restricted Boltzmann Machines for Modeling Motion Style Graham W. Taylor GWTAYLOR @ CS . TORONTO . EDU Geoffrey E. Hinton Add to Reading List Source URL: www.machinelearning.org Language: English - Date: 2009-05-18 12:17:00 Probability and statistics Neural networks Machine learning Boltzmann machine Generative model Graphical model Hidden Markov model Bayesian network Ludwig Boltzmann Statistical models Statistics Bayesian statistics
307	Dynamical Products of Experts for Modeling Financial Time Series Add to Reading List Source URL: www.icml2010.org Language: English - Date: 2010-06-13 09:06:37 Econometrics Time series analysis Autoregressive conditional heteroskedasticity Options Markov models Stochastic volatility Time series Volatility Markov chain Statistics Mathematical finance Probability and statistics
308	Bias and Variance in Value Function Estimation Shie Mannor [removed] Laboratory for Information and Decision Systems, Massachusetts Institute of Technology, Cambridge, MA[removed]Duncan Simester [removed] Add to Reading List Source URL: www.machinelearning.org Language: English - Date: 2008-12-01 11:19:51 Statistical theory Probability theory Variance Normal distribution Standard deviation Estimation theory Markov chain Autoregressive conditional heteroskedasticity Bias of an estimator Statistics Data analysis Summary statistics
309	Dynamic Conditional Random Fields: Factorized Probabilistic Models for Labeling and Segmenting Sequence Data Charles Sutton Khashayar Rohanimanesh Andrew McCallum Add to Reading List Source URL: www.machinelearning.org Language: English - Date: 2008-12-01 11:19:43 Probability and statistics Probability Machine learning Bayesian statistics Statistical models Conditional random field Sequence labeling Hidden Markov model Part-of-speech tagging Statistics Markov models Graphical models
310	Unsupervised Evidence Integration Philip M. Long Vinay Varadan Sarah Gilman Mark Treshock Add to Reading List Source URL: www.machinelearning.org Language: English - Date: 2008-12-01 11:14:16 Statistical dependence Graphical models Expectation–maximization algorithm Missing data Conditional independence Variance Independence Algorithm Maximum likelihood Statistics Probability theory Estimation theory

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