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» Introduction to Monte Carlo simulation
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IJBC
2008
96views more  IJBC 2008»
14 years 8 months ago
Fractional Processes: from Poisson to Branching One
Fractional generalizations of the Poisson process and branching Furry process are considered. The link between characteristics of the processes, fractional differential equations ...
V. V. Uchaikin, D. O. Cahoy, R. T. Sibatov
SAC
2010
ACM
14 years 8 months ago
Importance tempering
Simulated tempering (ST) is an established Markov Chain Monte Carlo (MCMC) methodology for sampling from a multimodal density π(θ). The technique involves introducing an auxilia...
Robert B. Gramacy, Richard Samworth, Ruth King
SCANGIS
2003
14 years 11 months ago
The Issue of Uncertainty Propagation in Spatial Decision Making
GISs give users facilities to integrate and analyze data from different sources with different scale, accuracy, resolution and quality of the original data which are the key aspect...
Rahim Ali. Abbaspour, Mahmoud Reza Delavar, Reihan...
MP
2006
107views more  MP 2006»
14 years 9 months ago
Convergence theory for nonconvex stochastic programming with an application to mixed logit
Monte Carlo methods have been used extensively in the area of stochastic programming. As with other methods that involve a level of uncertainty, theoretical properties are required...
Fabian Bastin, Cinzia Cirillo, Philippe L. Toint
WSC
2004
14 years 11 months ago
New Event-driven Sampling Techniques for Network Reliability Estimation
Exactly computing network reliability measures is an NPhard problem. Therefore, Monte Carlo simulation has been frequently used by network designers to obtain accurate estimates. ...
Abdullah Konak, Alice E. Smith, Sadan Kulturel-Kon...