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))