Monte Carlo Simulation and Derivation of Chi-Square Statistics

Derivation and validation of a sensitivity formula for knife-edge slit gamma camera: A theoretical and Monte Carlo simulation study

Introduction: Gamma cameras are proposed for online range verification and treatment monitoring in proton therapy.  An Analytical formula was derived and validated for sensitivity of a slit collimator based on the photon fluence concept. Methods: Fluence formulation was generalized for photons distribution function and solved for high-energy point sources. The...

Chi-Square Statistics with Multiple Imputation

Monte Carlo Simulation of Magnetic Systems in the Tsallis Statistics

We apply the Broad Histogram Method to an Ising system in the context of the recently reformulated Generalized Thermostatistics, and we claim it to be a very efficient simulation tool for this non-extensive statistics. Results are obtained for the nearest-neighbour version of the Ising model for a range of values of the q parameter of Generalized Thermostatistics. We found an evidence that the ...

Monte Carlo and Quasi-Monte Carlo for Statistics

This article reports on the contents of a tutorial session at MCQMC 2008. The tutorial explored various places in statistics where Monte Carlo methods can be used. There was a special emphasis on areas where Quasi-Monte Carlo ideas have been or could be applied, as well as areas that look like they need more research.

Monte Carlo Methods in Statistics

is converging to the expectation Ef [h(X)] when T goes to infinity. Furthermore, the precision of this approximation is exactly of the same kind as the precision of a statistical estimate, in that it usually evolves as O( √ T ). Therefore, once a sample x1, . . . , xT is produced according to a distribution density f , all standard statistical tools, including bootstrap, apply to this sample (w...