Results 41 to 50 of about 676,552 (170)

Monte Carlo investigation of S-values for 111In radionuclide therapy

Brazilian Journal of Radiation Sciences, 2023
Novel therapeutic strategy in radionuclide therapy use cell-penetrating monoclonal antibodies to carry Auger-emitting radionuclides into the cells. Estimation of dose in normal and tumor cells are important to investigate the efficacy and toxicity of ...
Masoud Jabbari, S Pandesha
doaj   +1 more source

Monte Carlo simulation of boson lattices

, 2006
Boson lattices are theoretically well described by the Hubbard model. The basic model and its variants can be effectively simulated using Monte Carlo techniques.
Nightingale M. P., OLAV F. SYLJUÅSEN, VESA APAJA   +2 more
core   +1 more source

MCSim: A Monte Carlo Simulation Program

Journal of Statistical Software, 1997
MCSim consists of two pieces, a model generator and a simulation engine. The model generator, mod, was created to facilitate the model maintenance and simulation definition, while keeping execution time fast.
Frédéric Y. Bois, Don R. Maszle
doaj   +3 more sources

Quasi-Monte Carlo simulation of Brownian sheet with application to option pricing

Statistical Theory and Related Fields, 2017
Monte Carlo and quasi-Monte Carlo methods are widely used in scientific studies. As quasi-Monte Carlo simulations have advantage over ordinary Monte Carlo methods, this paper proposes a new quasi-Monte Carlo method to simulate Brownian sheet via its ...
Xinyu Song, Yazhen Wang
doaj   +1 more source

PENGGUNAAN SIMULASI MONTE CARLO DALAM ESTIMASI VALUE AT RISK (VaR) PORTOFOLIO YANG DIBENTUK DARI INDEKS HARGA SAHAM MULTINASIONAL

E-Jurnal Matematika, 2022
Investment is buying an asset that is expected in the future can be resold and get a high profit value. There are two factors that must be considered when you want to invest in stocks, namely the rate of return on stocks and risk factors.
NABILA NUR JANNAH, KOMANG DHARMAWAN, LUH PUTU IDA HARINI   +2 more
doaj   +1 more source

Transition Matrix Monte Carlo

, 1999
Although histogram methods have been extremely effective for analyzing data from Monte Carlo simulations, they do have certain limitations, including the range over which they are valid and the difficulties of combining data from independent simulations.
BRIAN DIGGS, CHRISTOPHER GENOVESE, de Oliveira P. M. C., JIAN-SHENG WANG, JOSEPH B. KADANE, ROBERT H. SWENDSEN, SHING-TE LI   +6 more
core   +1 more source

High Ener High Energy Appr gy Approximation for Monte Carlo E ximation for Monte Carlo Event gener ent generator

Eurasian Journal of Physics and Functional Materials
Analysis of the nuclear physics experiment often requires Monte Carlo simulation of the detector setup. Such kind of simulations often requires a quite advanced model of nuclear interaction.
A. N. Ismailova , Yu. L. Parfenova , P. G. Sharov, D. M. Janseitov   +3 more
doaj   +1 more source

Spreadsheet Data Resampling for Monte-Carlo Simulation

Spreadsheets in Education, 2008
The pervasiveness of spreadsheet software resulted in its increased application as a simulation tool for business analysis. Random values generation supporting such evaluations using spreadsheets are simple and yet powerful. However, the typical approach
Thin Yin Leong, Wee Leong Lee
doaj  

Monte Carlo simulation of ice models

, 1997
We propose a number of Monte Carlo algorithms for the simulation of ice models and compare their efficiency. One of them, a cluster algorithm for the equivalent three colour model, appears to have a dynamic exponent close to zero, making it particularly ...
[H. G. Evertz, A. Rahman, A. Yanagawa, E. Carlon, E. H. Lieb, E. H. Lieb, E. H. Lieb, F. Rys, G. T. Barkema, H. J. F. Knops, H. Saleur, J. C. Slater, J. D. Bernal, J. Kondev, J.-S. Wang, L. Pauling, M. E. J. Newman, M. P. Nightingale, N. Bjerrum, N. Bjerrum, P. V. Hobbs, R. H. Swendsen, R. J. Baxter, R. Raghavan, U. Wolff   +24 more
core   +3 more sources

Monte Carlo simulation of grain growth

Materials Research, 1999
Understanding and predicting grain growth in Metallurgy is meaningful. Monte Carlo methods have been used in computer simulations in many different fields of knowledge. Grain growth simulation using this method is especially attractive as the statistical
Paulo Blikstein, André Paulo Tschiptschin   +1 more
doaj   +1 more source