new monte carlo approach
A New Approach to Monte Carlo Simulation of Operations
... Quantum Monte Carlo methods solve the many-body problem for quantum ...physics, Monte Carlo methods are used for designing detectors, understanding their behavior and comparing experimental ...
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A non iterative (trivial) method for posterior inference in stochastic volatility models
... a new non-iterative, very simple, Bayesian inference procedures for the stochastic volatility ...our approach is to solve this linear ...direct Monte Carlo yielding independent samples from ...
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Appropriation of the ‘Witch’ Stigma as White Women's Self-Empowerment
... the Monte Carlo method refers to a technique through which random numbers are used to solve ...With new advancements in electronic computing occurring at the time, Ulam envisioned the application of ...
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Sequential Monte Carlo with transformations
... this approach to initialise MCMC on (in this case, a space of graphs), t + 1 sequences using the output of MCMC on t sequences, and TreeMix (Pickrell and Pritchard 2012) uses a similar idea in a greedy ...
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Towards automatic model comparison : an adaptive sequential Monte Carlo approach
... a new approach to adaptation and guidelines on the near-automatic implementation of the proposed ...proposed approach is compared with state-of-the-art alternatives in extensive simulation studies ...
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Bayesian inversion of a CRN depth profile to infer Quaternary erosion of the northwestern Campine Plateau (NE Belgium)
... version approach has two new ingredients: it (1) uses Markov chain Monte Carlo (MCMC) sampling, and (2) accounts for (under certain conditions) the contribution of model errors to posterior ...
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Cascade source inference in networks: a Markov chain Monte Carlo approach
... a new hat, her classmates may or may not imitate the purchase depending on how they agree with her ...Alice’s new hat, though they may still be persuaded by someone they appreciate ...
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Simulating the drug discovery pipeline: a Monte Carlo approach
... launched new molecular entities (NME) has at best been flat while costs have risen, resulting in a sharp decline in the number of first-in-class drugs entering the market as a percentage of R&D expenditures ...
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Ultra-fast Carrier Transport Simulation on the Grid. Quasi-Random Approach
... quasirandom approach for ultrafast carrier transport ...of Monte Carlo methods do not give adequate ...obtain new estimates about important physical quanti- ...
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A Data Association Algorithm for Multiple Object Tracking in Video Sequences
... The Monte Carlo approach relies on a sample- based construction to represent the state pdf. Mul- tiple particles (samples) of the state are generated, each one associated with a weight which charac- ...
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Monte Carlo sampling approach to stochastic programming
... the Monte Carlo approach are the interior and exterior ...with new (independent) or updated samples generated in the process of iterations, ...
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Multilevel and quasi Monte Carlo methods for uncertainty quantification in particle travel times through random heterogeneous porous media
... this approach is that it only requires a single eigen-decomposition of the covariance matrix, the results of which are stored and used to generate new realizations of the permeability field very cheaply, ...
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An Improved Clustering based Monte Carlo Localization approach for Cooperative Multi-robot Localization
... probabilistic approach for cooperative multi-robot localization in indoor ...Our approach is based on Monte Carlo localization that has been applied with great practical success to single ...
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Distinguishing Migration From Isolation: A Markov Chain Monte Carlo Approach
... Metropolis-Hastings MCMC: To evaluate the integral in (2) it is necessary to use Monte Carlo methods. As in Wilson and Balding (1998) and Nielsen (2000a), it is possible to define a Markov chain with state ...
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Level densities of heavy nuclei in the shell model Monte Carlo approach
... Quantum Monte Carlo methods are often limited by the so-called sign problem, which leads to large statistical ...good Monte Carlo sign in the grand canonical ensemble and the sign remains good ...
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A Multivariate Analysis for Risk Capital Estimation in Insurance Industry: Vine Copulas
... At first sight, we notice immediately that the capital requirement assessed with vine copula is less than the capital requirement evaluated under the independence assumption. The estimation results show that the way in ...
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A Probabilistic Monte Carlo model for pricing discrete barrier options
... Broadie et al. (1997) showed 'that discrete barrier options can be priced with remarkable accuracy using continuous barrier formulas by applying a simple continuity correction to the barrier'. The approximation is ...
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The jackknife in Monte Carlo studies
... 4 Monte Carlo summaries (RB, RV, Skew, Kurt) are ratios of correlated sample moments computed from the Monte Carlo result matrix X of N = 4 , 000 independent ...
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Research on cold chain in food industry in China
... have standard errors associated with the estimates. However, many times the analyst or decision maker will be confronted with variables for which there are no such forecasting models, such as applying some new ...
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MONTE CARLO SIMULATION OF TECHNOLOGICAL RISKS IN CHICKEN PRODUCTION IN A BAYESIAN APPROACH
... of breeding a laying-hen population by a simulation program based on the mathematical combination of Bayes’ statistics and a Monte Carlo simulation, developed by our team in c# programming language. On one ...
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