This preview has intentionally blurred sections. Sign up to view the full version.
View Full DocumentThis preview has intentionally blurred sections. Sign up to view the full version.
View Full DocumentThis preview has intentionally blurred sections. Sign up to view the full version.
View Full DocumentThis preview has intentionally blurred sections. Sign up to view the full version.
View Full DocumentThis preview has intentionally blurred sections. Sign up to view the full version.
View Full Document
Unformatted text preview: U u u F x x π AcceptReject Method f. to according d distribute is Y variate The otherwise 1 Return to . 3 Mg(X) f(X) U if X Y Accept 2. Unif(0,1) ~ U g, ~ X Generate 1. constant. a is M where x, all for Mg(x) f(x) such that pdfs be g and f Let ≤ = ≤ Example N(0,1) from generate to method reject accept apply the can Then we . e 2/ M Hence 1. at x attained is which , by bounded is ) 1 ( g(x) f(x) Now, on. distributi N(0,1) from generate want to We ons. distributi ) Cauchy(0,1 and N(0,1) of pdfs be g and f Suppose 2 2 2 = ± = + =x e x Discrete Distributions ) p (Assume k. X put then p If Unif(0,1). ~ U Generate . be X variable random the of on distributi y probabilit Let the 1k 2 1 2 1 = = ≤ < k n n p U p p p x x x...
View
Full Document
 Spring '09
 ProfLaha
 Normal Distribution, Probability theory, Cauchy distribution

Click to edit the document details