forder {evd} | R Documentation |

## Maximum-likelihood Fitting of Order Statistics

### Description

Maximum-likelihood fitting for the distribution of a selected order statistic of a given number of independent variables from a specified distribution.

### Usage

```
forder(x, start, densfun, distnfun, ..., distn, mlen = 1, j = 1,
largest = TRUE, std.err = TRUE, corr = FALSE, method = "Nelder-Mead")
```

### Arguments

`x` |
A numeric vector. |

`start` |
A named list giving the initial values for the parameters over which the likelihood is to be maximized. |

`densfun` , `distnfun` |
Density and distribution function of the specified distribution. |

`...` |
Additional parameters, either for the specified
distribution or for the optimization function |

`distn` |
A character string, optionally specified as an alternative
to |

`mlen` |
The number of independent variables. |

`j` |
The order statistic, taken as the |

`largest` |
Logical; if |

`std.err` |
Logical; if |

`corr` |
Logical; if |

`method` |
The optimization method (see |

### Details

Maximization of the log-likelihood is performed. The estimated standard errors are taken from the observed information, calculated by a numerical approximation.

If the density and distribution functions are user defined, the order
of the arguments must mimic those in R base (i.e. data first,
parameters second).
Density functions must have `log`

arguments.

### Value

Returns an object of class `c("extreme","evd")`

.
This class is defined in `fextreme`

.

The generic accessor functions `fitted`

(or
`fitted.values`

), `std.errors`

,
`deviance`

, `logLik`

and
`AIC`

extract various features of the
returned object.
The function `anova`

compares nested models.

### See Also

### Examples

```
uvd <- rorder(100, qnorm, mean = 0.56, mlen = 365, j = 2)
forder(uvd, list(mean = 0, sd = 1), distn = "norm", mlen = 365, j = 2)
forder(uvd, list(rate = 1), distn = "exp", mlen = 365, j = 2,
method = "Brent", lower=0.01, upper=10)
forder(uvd, list(scale = 1), shape = 1, distn = "gamma", mlen = 365, j = 2,
method = "Brent", lower=0.01, upper=10)
forder(uvd, list(shape = 1, scale = 1), distn = "gamma", mlen = 365, j = 2)
```

*evd*version 2.3-7 Index]