Dr. Hackney STA Solutions pg 84

# Dr. Hackney STA Solutions pg 84 - 5-18 Solutions Manual for...

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Unformatted text preview: 5-18 Solutions Manual for Statistical Inference b. fX (x) = e-(log x-) 1 x 2 2 /2 2 . Let V gamma(, ) where 2 (e+( /2) )2 = 2(+2 ) , e - e2+2 since given and 2 we can set e2(+ ) - e2+ and = , e+(2 /2) 2 2 EV = = e+( and Var(V ) = 2 = e2(+ Now, follow the algorithm on page 254. c. fX (x) = e -x 2 2 /2) = EX 2 ) - e2+ = Var(X). x-1 . Let V exponential(). Now, follow the algorithm on page 254 where i = min Vi-1 -Vi -1 e Zi-1 +V -Z i i-1 +Zi-1 ,1 An R code to generate a sample size of 100 from a Weibull(3,2) is: #initialize a and b b <- 2 a <- 3 Z <- rexp(1,1/b) ranvars <- matrix(c(Z),byrow=T,ncol=1) for( i in seq(2000)) { U <- runif(1,min=0,max=1) V <- rexp(1,1/b) p <- pmin((V/Z)^(a-1)*exp((-V^a+V-Z+Z^a)/b),1) if (U <= p) Z <- V ranvars <- cbind(ranvars,Z) } #One option: choose elements in position 1001,1002,...,1100 to be the sample vector.1 <- ranvars[1001:1100] mean(vector.1) var(vector.1) #Another option: choose elements in position 1010,1020,...,2000 to be the sample vector.2 <- ranvars[seq(1010,2000,10)] mean(vector.2) var(vector.2) Output: [1] 1.048035 [1] 0.1758335 [1] 1.130649 [1] 0.1778724 5.69 Let w(v, z) = fY (v)fV (z) fV (v)fY (z) , and then (v, z) = min{w(v, z), 1}. We will show that Zi fY P (Zi+1 a) = P (Y a). ...
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## This note was uploaded on 02/03/2012 for the course STA 1014 taught by Professor Dr.hackney during the Spring '12 term at UNF.

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