## fit a normal distribution by ML
# generate a variable from normally distributed random numbers
x <- rnorm( 100, 1, 2 )
# log likelihood function (for individual observations)
llf <- function( param ) {
return( dnorm( x, mean = param[ 1 ], sd = param[ 2 ], log = TRUE ) )
}
## ML method
ml <- maxLik( llf, start = c( mu = 0, sigma = 1 ) )
# return number of onservations
nObs( ml )
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