powered by
The maximum likelihood estimate of mean is the empirical mean and the maximum likelihood estimate of sd is the square root of the biased sample variance.
mean
sd
mlnorm(x, na.rm = FALSE, ...)
mlnorm returns an object of class
mlnorm
univariateML. This is a named numeric vector with maximum likelihood estimates for mean and sd and the following attributes:
univariateML
model
The name of the model.
density
The density associated with the estimates.
logLik
The loglikelihood at the maximum.
support
The support of the density.
n
The number of observations.
call
The call as captured my match.call
match.call
a (non-empty) numeric vector of data values.
logical. Should missing values be removed?
currently affects nothing.
For the density function of the normal distribution see Normal.
Johnson, N. L., Kotz, S. and Balakrishnan, N. (1995) Continuous Univariate Distributions, Volume 1, Chapter 13. Wiley, New York.
Normal for the normal density.
mlnorm(precip)
Run the code above in your browser using DataLab