Monte carlo and quasi-monte carlo methods 2006 / by International Conference on Monte Carlo and Quasi-Monte Carlo Methods in Scientific Computing (7th : 2006 : Ulm, Germany), Keller, Alexander, 1968-, Heinrich, Stefan, Niederreiter, Harald, 1944-

Subjects:

Monte Carlo methods / by 204054 Kalos, Malvin H., Whitlock, Paula A.

Subjects: “…Monte Carlo method…”

The Monte Carlo method / by Sobol, I. M. (Ilia Meerovich)

Subjects: “…Monte Carlo method…”

Monte Carlo methods / by 219862 Hammersley, John Michael, Handscomb, David Christopher

Relativistic Monte Carlo by Lu, X, Perrone, V, Hasenclever, L, Teh, Y, Vollmer, S

“…Hamiltonian Monte Carlo (HMC) is a popular Markov chain Monte Carlo (MCMC) algorithm that generates proposals for a Metropolis-Hastings algorithm by simulating the dynamics of a Hamiltonian system. …”

Simulation and the monte carlo method / by 296842 Rubinstein, Reuven Y., Kroese, Dirk P.

Subjects: “…Monte Carlo method…”

Simulation and the Monte Carlo method / by 296842 Rubinstein, Reuven Y.

Subjects: “…Monte Carlo method…”

Monte Carlo methods for electromagnetics / by 357638 Sadiku, Matthew N. O.

Subjects:

Monte Carlo methods in finance / by 189076 Jackel, Peter

Subjects: “…Monte Carlo method…”

Monte Carlo simulation and finance / by 267966 McLeish, Don L.

Subjects:

Exploring Monte Carlo methods / by Dunn, William L. (William Lee), 1944-, Shultis, J. Kenneth.

Subjects: “…Monte Carlo method…”

Monte Carlo Simulation and Applications by Abd Al Kareem I Sheet, Nadia Adeel Saeed

Subjects: “…Monte Carlo…”
Get full text

Monte Carlo Experimentation in Econometrics. by Hendry, D

Nonparametric Hamiltonian Monte Carlo by Mak, C, Zaiser, F, Ong, L

“…This paper introduces the Nonparametric Hamiltonian Monte Carlo (NP-HMC) algorithm which generalises HMC to nonparametric models. …”

Vibrato Monte Carlo sensitivities by Giles, M

“…We show how the benefits of the pathwise sensitivity approach to computing Monte Carlo Greeks can be extended to discontinuous payoff functions through a combination of the pathwise approach and the Likelihood Ratio Method. …”

Sequential Monte Carlo samplers by Del Moral, P, Doucet, A, Jasra, A

“…These probability distributions are approximated by a cloud of weighted random samples which are propagated over time by using sequential Monte Carlo methods. This methodology allows us to derive simple algorithms to make parallel Markov chain Monte Carlo algorithms interact to perform global optimization and sequential Bayesian estimation and to compute ratios of normalizing constants. …”

Controlled sequential Monte Carlo by Heng, J, Bishop, A, Deligiannidis, G, Doucet, A

“…Sequential Monte Carlo methods, also known as particle methods, are a popular set of techniques for approximating high-dimensional probability distributions and their normalizing constants. …”

Kernel sequential Monte Carlo by Schuster, I, Strathmann, H, Paige, B, Sejdinovic, D

“…We propose kernel sequential Monte Carlo (KSMC), a framework for sampling from static target densities. …”

Multilevel Monte Carlo methods by Giles, M

Sequential Monte Carlo with transformations by Everitt, RG, Culliford, R, Medina-Aguayo, F, Wilson, DJ

“…For this, we use sequential Monte Carlo samplers, introducing the innovation of using deterministic transformations to move particles effectively between target distributions with different dimensions. …”