Maximum Likelihood Parameter Estimates for Asymmetric Distributions

DESCRIPTION:

Maximum likelihood parameter estimation for gamma, lognormal, and Weibull distributions.

USAGE:

gammaMLE(data, save.data=T, control=weibullMLE.control(...), ...)
lognormMLE(data, save.data=T)
weibullMLE(data, save.data=T, control=weibullMLE.control(...), ...)

REQUIRED ARGUMENTS:

data
a vector of positive real numbers.

OPTIONAL ARGUMENTS:

control
a list of control parameters. Use the functions gammaMLE.control and weibullRob.control (respectively) to create the control list.
save.data
if TRUE the vector of data is included in the returned object.
...
control arguments may be passed directly.

VALUE:

an asymmetric.dstn object with class "gammaMLE", "lognormMLE", or "weibullMLE" (respectively) containing the following components.
call
an image of the call that produced the object, but with the arguments all named.
mu
maximum likelihood estimate of the mean.
alpha
maximum likelihood estimate of the shape parameter.
sigma
maximum likelihood estimate of the scale parameter.
V.mu
maximum likelihood estimate of the variance of mu.
data
the data if data=T.
cov
an estimate of the covariance of alpha and sigma (gamma and Weibull only).
nit
number of iterations (gamma and Weibull only).

SEE ALSO:

, , , .

EXAMPLES:

gammaMLE(los)
gammaMLE(los, tol=1e-5)
gammaMLE(los, control = gammaMLE.control(tol=1e-5))