<--- Back to Details
First PageDocument Content
Statistics / Monte Carlo software / Stan / Statistical models / Rasch / MCMC / Hybrid Monte Carlo
Date: 2016-01-27 05:30:15
Statistics
Monte Carlo software
Stan
Statistical models
Rasch
MCMC
Hybrid Monte Carlo

Fast Bayesian modeling in Stan using rstan mc-stan.org

Add to Reading List

Source URL: www.londonr.org

Download Document from Source Website

File Size: 577,67 KB

Share Document on Facebook

Similar Documents

Statistics / Monte Carlo software / Stan / Statistical models / Rasch / MCMC / Hybrid Monte Carlo

Fast Bayesian modeling in Stan using rstan mc-stan.org

DocID: 1qMm2 - View Document

Monte Carlo methods / Molecular modelling / Computational chemistry / Markov chain Monte Carlo / Molecular dynamics / Hybrid Monte Carlo / Stochastic / Monte Carlo molecular modeling / Modeling of polymer crystals

9th AIMS CONFERENCE – ABSTRACTS 24 Special Session 5: Hybrid Monte Carlo Elena Akhmatskaya, Basque Center for Applied Mathematics, Spain

DocID: 1oUAe - View Document

Statistics / 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

DocID: 1ofcO - View Document

Estimation theory / Linear filters / Control theory / Robot control / Monte Carlo methods / Kalman filter / Particle filter / Data assimilation / Lagrangian mechanics / Lagrangian / Drifter / NavierStokes equations

A hybrid particle-ensemble Kalman filter for high dimensional Lagrangian data assimilation Laura Slivinski1 , Elaine Spiller2 , and Amit Apte3 1 3

DocID: 1mpmX - View Document

On Probabilistic Results for the Discrepancy of a Hybrid-Monte Carlo Sequence Michael Gnewuch Department of Computer Science, University of Kiel, Christian-Albrechts-Platz 4, 24098 Kiel, Germany email:

DocID: 1h2lW - View Document