Results 11 to 20 of about 1,208,874 (255)
Multilevel Monte Carlo for continuous time Markov chains, with applications in biochemical kinetics [PDF]
, 2012 We show how to extend a recently proposed multi-level Monte Carlo approach to the continuous time Markov chain setting, thereby greatly lowering the computational complexity needed to compute expected values of functions of the state of the system to a ...
Anderson, David, Higham, Desmond
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High performance Monte Carlo computation for finance risk data analysis [PDF]
, 2013 This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.Finance risk management has been playing an increasingly important role in the finance sector, to analyse finance data and to prevent any potential crisis ...
Zhao, Yu
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Why Monte Carlo Simulations are Inferences and not Experiments [PDF]
, 2012 Monte Carlo Simulations arrive at their results by introducing randomness, sometimes derived from a physical randomizing device. Nonetheless, we argue, they open no new epistemic channels beyond that already employed by traditional simulations: the ...
John D. Norton +3 more
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SMCTC : sequential Monte Carlo in C++ [PDF]
, 2009 Sequential Monte Carlo methods are a very general class of Monte Carlo methods for sampling from sequences of distributions. Simple examples of these algorithms are used very widely in the tracking and signal processing literature.
Johansen, Adam M., Adam M. Johansen
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Geodesic Monte Carlo on Embedded Manifolds [PDF]
, 2013 Markov chain Monte Carlo methods explicitly defined on the manifold of probability distributions have recently been established. These methods are constructed from diffusions across the manifold and the solution of the equations describing geodesic flows
Simon Byrne +5 more
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Information-Geometric Markov Chain Monte Carlo Methods Using Diffusions [PDF]
, 2014 Recent work incorporating geometric ideas in Markov chain Monte Carlo is reviewed in order to highlight these advances and their possible application in a range of domains beyond statistics. A full exposition of Markov chains and their use in Monte Carlo
Livingstone, Samuel +5 more
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PERHITUNGAN VaR PORTOFOLIO SAHAM MENGGUNAKAN DATA HISTORIS DAN DATA SIMULASI MONTE CARLO
E-Jurnal Matematika, 2012 Value at Risk (VaR) is the maximum potential loss on a portfolio based on the probability at a certain time. In this research, portfolio VaR values calculated from historical data and Monte Carlo simulation data.
WAYAN ARTHINI +2 more
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Frequency-resolved Monte Carlo
Scientific Reports, 2018 We adapt the Quantum Monte Carlo method to the cascaded formalism of quantum optics, allowing us to simulate the emission of photons of known energy. Statistical processing of the photon clicks thus collected agrees with the theory of frequency-resolved ...
Juan Camilo López Carreño +2 more
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E-Jurnal Matematika, 2017 Contract options are the most important part of an investment strategy. An option is a contract that entitles the owner or holder to sell an asset on a designated maturity date.
DEWA AYU AGUNG PUTRI RATNASARI +2 more
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Automatic differentiable Monte Carlo: Theory and application
Physical Review Research, 2023 Differentiable programming has emerged as a key programming paradigm empowering rapid developments of deep learning while its applications to important computational methods such as Monte Carlo remain largely unexplored.
Shi-Xin Zhang, Zhou-Quan Wan, Hong Yao
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