R: Maximum-likelihood Fitting of Univariate Distributions

fitdstn {robust} | R Documentation

## Maximum-likelihood Fitting of Univariate Distributions

### Description

Maximum-likelihood fitting of univariate distributions.

### Usage

    fitdstn(x, densfun, ...)

### Arguments

`x` | a numeric vector containing the sample.
`densfun` | a character string naming the distribution. Distributions ‘gamma’, ‘lognormal’, and ‘weibull’ are supported.
`...` | additional arguments are ignored.

### Details

This function relies on the `fitdistr` function for the computations. The returned object is modified to support plotting and comparison.

### Value

a list with class “fitdstn” containing the following elements:

`estimate` | a named numeric vector containing the parameter estimates.
`sd` | a named numeric vector containing the standard deviations of the parameter estimates.
`vcov` | a numeric matrix containing the variance-covariance matrix of the estimated parameter vector.
`n` | a single numeric value indicating the number of sample points in `x`.
`loglik` | a single numeric value giving the maxized the log-likelihood.
`call` | the matched call.
`densfun` | the character string `densfun` provided in the arguments.
`x` | the data provided in `x`.

### Note

The `print` method displays the estimated parameters and their standard errors (in parentheses).

### See Also

An important goal here is the comparison with robust fits to the same distributions, see `fitdstnRob`.

`fitdistr` which provides many more choices for `densfun`.

[Package robust version 0.5-0.0 Index]