| mlnorm {univariateML} | R Documentation |
Normal distribution maximum likelihood estimation
Description
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.
Usage
mlnorm(x, na.rm = FALSE, ...)
Arguments
x |
a (non-empty) numeric vector of data values. |
na.rm |
logical. Should missing values be removed? |
... |
currently affects nothing. |
Details
For the density function of the normal distribution see Normal.
Value
mlnorm returns an object of class univariateML.
This is a named numeric vector with maximum likelihood estimates for
mean and sd and the following attributes:
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 |
References
Johnson, N. L., Kotz, S. and Balakrishnan, N. (1995) Continuous Univariate Distributions, Volume 1, Chapter 13. Wiley, New York.
See Also
Normal for the normal density.
Examples
mlnorm(precip)