Statistical models

Results: 4614



#Item
341Graphical models / Statistical models / Statistical inference / Bayesian network / Networks / Bayesian statistics / Bayesian / Joint probability distribution / Bayesian inference

Analysis  of  Massive  Data  Streams   using  R  and  AMIDST   Page 9 of 73 FP7-ICTAMIDST

Add to Reading List

Source URL: static.amidst.eu

Language: English - Date: 2015-07-05 06:50:14
342Estimation theory / Statistical theory / Identifiability / Econometrics / Statistical models

MONFISPOL Grant no.: DeliverableDevelopment of the combined approach for assessing identification in the prior space of model parameters. Software prototype Joint Research Centre, European Commission

Add to Reading List

Source URL: www.monfispol.eu

Language: English - Date: 2011-04-20 14:05:39
343Networks / Statistical models / Nir Friedman / Gene regulatory network / Bayesian network / Thank You / Algorithm / Graphical model / Causality

FROM GENE EXPRESSION TO MOLECULAR PATHWAYS T HESIS SUBMITTED FOR THE DEGREE OF “D OCTOR OF P HILOSOPHY ” BY

Add to Reading List

Source URL: www.cs.huji.ac.il

Language: English - Date: 2015-08-10 08:23:34
344Regression analysis / Econometrics / Statistical methods / Statistical models / Senescence / Survival analysis / Covariate / Least squares / Errors and residuals / Proportional hazards model / Propensity score matching

RISK EVALUATION AFTER HEART VALVE REPLACEMENT BY SAS PROC PHREG Chao L. Chen and Lynn Wang Deborah Heart and Lung Center, Browns Mills, NJSUMMARY Identification of long-term risk factors after heart valve replacem

Add to Reading List

Source URL: www.ats.ucla.edu

Language: English - Date: 2016-08-17 18:18:26
345Statistical models / Bayesian network / Graphical model / Nir Friedman / Hidden variable theory / Causality / Expectationmaximization algorithm / Expected value / Latent variable

LEARNING HIDDEN VARIABLES IN PROBABILISTIC GRAPHICAL MODELS T HESIS SUBMITTED FOR THE DEGREE OF

Add to Reading List

Source URL: www.cs.huji.ac.il

Language: English - Date: 2015-08-10 08:23:23
346Regression analysis / Econometrics / Actuarial science / Statistical models / Scientific method / Logistic regression / Generalized linear model / Generalized additive model / Prediction / Homework / Multinomial logistic regression / Statistics

Statistics 149 Statistical Sleuthing through Generalized Linear Models Spring 2016 Lectures: Mon/Wed, 1:00pm–2:30pm, Sci Ctr E Instructor: Mark E. Glickman, Sci Ctr 605 E-mail:

Add to Reading List

Source URL: www.glicko.net

Language: English - Date: 2016-07-26 13:40:09
347

May 2016 EMF/EAA JOINT PAPER ON THE USE OF AUTOMATED VALUATION MODELS IN EUROPE Summary of Findings Automated Valuation Models (AVMs) are statistical valuation solutions providing an estimate of value of any specified pr

Add to Reading List

Source URL: www.europeanavmalliance.org

Language: English - Date: 2016-05-11 08:17:48
    348Network theory / Graph theory / Networks / Statistical models / Algebraic graph theory / Community structure / Modularity / Connectivity / Bayesian network / Graphical model / Graph / Clique

    Is Holism A Problem For Inductive Inference? A Computational Analysis Maxwell A. Bertolero () Thomas L. Griffiths (tom ) Department of Psychology & Helen Wills Neuroscience Ins

    Add to Reading List

    Source URL: cocosci.berkeley.edu

    Language: English - Date: 2014-05-02 14:06:19
    349Statistics / Monte Carlo methods / Statistical theory / Probability / Markov chain Monte Carlo / Markov models / Computational statistics / Probability distribution / MetropolisHastings algorithm / Markov chain / Normal distribution / Hybrid Monte Carlo

    Exploring the structure of mental representations by implementing computer algorithms with people Adam N. Sanborn University of Warwick Thomas L. Griffiths

    Add to Reading List

    Source URL: cocosci.berkeley.edu

    Language: English - Date: 2014-10-06 13:14:45
    350Statistics / Machine learning / Statistical classification / Artificial intelligence / Ensemble learning / Statistical inference / Computational statistics / Support vector machine / Bootstrapping / Boosting / Naive Bayes classifier / Gradient boosting

    Automated Parameter Optimization of Classification Techniques for Defect Prediction Models Chakkrit Tantithamthavorn1 , Shane McIntosh2 , Ahmed E. Hassan3 , Kenichi Matsumoto1 1 Nara Institute of Science and

    Add to Reading List

    Source URL: sail.cs.queensu.ca

    Language: English - Date: 2016-02-19 18:06:49
    UPDATE