univariateML. This is a named numeric vector with maximum
likelihood estimates for shape1 and shape2 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 match.call
Arguments
x
a (non-empty) numeric vector of data values.
na.rm
logical. Should missing values be removed?
...
start contains optional starting parameter values for the
minimization, passed to the stats::nlm function. type specifies whether
a dedicated "gradient", "hessian", or "none" should be passed to
stats::nlm.
Details
For the density function of the Beta distribution see Beta.
For type, the option none is fastest.
References
Johnson, N. L., Kotz, S. and Balakrishnan, N. (1995)
Continuous Univariate Distributions, Volume 2, Chapter 25. Wiley, New York.
See Also
Beta for the Beta density, nlm for the
optimizer this function uses.