http://www.commres.net/ 2026-04-29T08:33:52+00:00 http://www.commres.net/ http://www.commres.net/_media/wiki/logo.png text/html 2026-03-17T22:51:07+00:00 Anonymous (anonymous@undisclosed.example.com) http://www.commres.net/estimated_standard_deviation/rout02?rev=1773787867&do=diff > rm(list=ls()) > > rnorm2 <- function(n,mean,sd){ + mean+sd*scale(rnorm(n)) + } > > # set.seed(191) > nx <- 1000 > mx <- 50 > sdx <- mx * 0.1 > sdx # 5 [1] 5 > x <- rnorm2(nx, mx, sdx) > # x <- rnorm2(1000, 50, 5) 와 동일 > > mean(x) [1] 50 > sd(x) [1] 5 > length(x) [1] 1000 > hist(x) > text/html 2026-03-17T22:58:49+00:00 Anonymous (anonymous@undisclosed.example.com) http://www.commres.net/estimated_standard_deviation/rscript02?rev=1773788329&do=diff rm(list=ls()) rnorm2 <- function(n,mean,sd){ mean+sd*scale(rnorm(n)) } # set.seed(191) nx <- 1000 mx <- 50 sdx <- mx * 0.1 sdx # 5 x <- rnorm2(nx, mx, sdx) # x <- rnorm2(1000, 50, 5) 와 동일 mean(x) sd(x) length(x) hist(x) # the above no gradient gradient <- function(x, v){ residuals = x - v # y = (sum(x-v)^2)/n 혹은 (mean(x-v)^2) # 의 식이 ms값을 구하는 식인데 # 이를 v에 대해서 미분하면 chain rule을 써야 한다 # 자세한 것은 http://commres.net/wiki/estimated_standard_deviation # 문서 중에 미분 부분 참조 …