Simulated Sample from Normal Distribution
The data set is used to understand the sampling variation of the score function. The simulated data is available in Pawitan (2001).
data(ns)
A data frame with 10 observations on the following 20 variables.
Sample.1a numeric vector
Sample.2a numeric vector
Sample.3a numeric vector
Sample.4a numeric vector
Sample.5a numeric vector
Sample.6a numeric vector
Sample.7a numeric vector
Sample.8a numeric vector
Sample.9a numeric vector
Sample.10a numeric vector
Sample.11a numeric vector
Sample.12a numeric vector
Sample.13a numeric vector
Sample.14a numeric vector
Sample.15a numeric vector
Sample.16a numeric vector
Sample.17a numeric vector
Sample.18a numeric vector
Sample.19a numeric vector
Sample.20a numeric vector
Pawitan, Y. (2001). In All Likelihood. Oxford Science Publications.
Pawitan, Y. (2001). In All Likelihood. Oxford Science Publications.
library(stats4)
data(ns)
x <- ns[,1]
nlogl <- function(mean,sd) { -sum(dnorm(x,mean=mean,sd=sd,log=TRUE)) }
norm_mle <- mle(nlogl,start=list(mean=median(x),sd=IQR(x)),nobs=length(x))
summary(norm_mle)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.