c(0:100,Inf) set.seed(1) (ps <- absdPsiMC(t, family="Gumbel", theta=2, degree=10, n.MC=10000, log=TRUE)) ## Note: The absolute value of the derivative at 0 should be Inf for ## Gumbel, however, it is always finite for the Monte Carlo approximation set.seed(1) ps2 <- absdPsiMC(log(t), family="Gumbel", theta=2, degree=10, n.MC=10000, log=TRUE, is.log.t = TRUE) stopifnot(all.equal(ps[-1], ps2[-1], tolerance=1e-14)) ## Now is there an advantage of using "is.log.t" ? sapply(eval(formals(absdPsiMC)$method), function(MM) absdPsiMC(780, family="Gumbel", method = MM, theta=2, degree=10, n.MC=10000, log=TRUE, is.log.t = TRUE)) ## not really better, yet...
first try
發表評論
所有評論
還沒有人評論,想成為第一個評論的人麼? 請在上方評論欄輸入並且點擊發布.