This class encapsulates results of a generic maximum likelihood procedure.

Objects can be created by calls of the form `new("mle", ...)`

, but
most often as the result of a call to `mle`

.

`call`

:Object of class

`"language"`

. The call to`mle`

.`coef`

:Object of class

`"numeric"`

. Estimated parameters.`fullcoef`

:Object of class

`"numeric"`

. Full parameter set of fixed and estimated parameters.`fixed`

:Object of class

`"numeric"`

. Fixed parameter values (`NA`

for non-fixed parameters).`vcov`

:Object of class

`"matrix"`

. Approximate variance-covariance matrix.`min`

:Object of class

`"numeric"`

. Minimum value of objective function.`details`

:a

`"list"`

, as returned from`optim`

.`minuslogl`

:Object of class

`"function"`

. The negative loglikelihood function.`nobs`

:`"integer"`

of length one. The number of observations (often`NA`

, when not set in call explicitly).`method`

:Object of class

`"character"`

. The optimization method used.

- confint
`signature(object = "mle")`

: Confidence intervals from likelihood profiles.- logLik
`signature(object = "mle")`

: Extract maximized log-likelihood.- profile
`signature(fitted = "mle")`

: Likelihood profile generation.- nobs
`signature(object = "mle")`

: Number of observations, here simply accessing the`nobs`

slot mentioned above.- show
`signature(object = "mle")`

: Display object briefly.- summary
`signature(object = "mle")`

: Generate object summary.- update
`signature(object = "mle")`

: Update fit.- vcov
`signature(object = "mle")`

: Extract variance-covariance matrix.

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