Major Components Probability distribution function Random number generator >Sampling rule >Scoring/Tallying >Error estimation Variance Reduction techniques Parallelization/Vectorization
Major Components Probability distribution function Random number generator Sampling rule Scoring/Tallying Error estimation Variance Reduction techniques Parallelization/Vectorization
Monte Carlo Example:Estimating n
Monte Carlo Example: Estimating π
Monte Carlo Example:Estimating n → If you are a very poor dart player,it is easy to imagine throwing darts randomly at the above figure,and it should be apparent that of the total number of darts that hit within the square,the number of darts that hit the shaded part(circle quadrant)is proportional to the area of that part.In other words, No.of darts hitting shaded area area of shaded area No.of darts hitting inside area area of square
If you are a very poor dart player, it is easy to imagine throwing darts randomly at the above figure, and it should be apparent that of the total number of darts that hit within the square, the number of darts that hit the shaded part (circle quadrant) is proportional to the area of that part. In other words, Monte Carlo Example: Estimating π No. of darts hitting shaded area area of shaded area No. of darts hitting inside area area of square