rweibull {evd} | R Documentation |

## The Reversed Weibull Distribution

### Description

Density function, distribution function, quantile function and
random generation for the reversed Weibull distribution with
location, scale and shape parameters.

### Usage

drweibull(x, loc=0, scale=1, shape=1, log = FALSE)
prweibull(q, loc=0, scale=1, shape=1, lower.tail = TRUE)
qrweibull(p, loc=0, scale=1, shape=1, lower.tail = TRUE)
rrweibull(n, loc=0, scale=1, shape=1)

### Arguments

`x, q` |
Vector of quantiles. |

`p` |
Vector of probabilities. |

`n` |
Number of observations. |

`loc, scale, shape` |
Location, scale and shape parameters (can be
given as vectors). |

`log` |
Logical; if `TRUE` , the log density is returned. |

`lower.tail` |
Logical; if `TRUE` (default), probabilities
are P[X <= x], otherwise, P[X > x] |

### Details

The reversed Weibull distribution function with parameters
`loc`

= a, `scale`

= b and
`shape`

= s is

*G(x) = exp{-[-(z-a)/b]^s}*

for *z < a* and one otherwise, where *b > 0* and
*s > 0*.

### Value

`drweibull`

gives the density function, `prweibull`

gives the distribution function, `qrweibull`

gives the
quantile function, and `rrweibull`

generates random deviates.

### Note

Within extreme value theory the reversed Weibull distibution is
usually referred to as the Weibull distribution.
I make a distinction to avoid confusion with the three-parameter
distribution used in survival analysis, which is related by a
change of sign to the distribution given above.

### See Also

`rfrechet`

, `rgev`

, `rgumbel`

### Examples

drweibull(-5:-3, -1, 0.5, 0.8)
prweibull(-5:-3, -1, 0.5, 0.8)
qrweibull(seq(0.9, 0.6, -0.1), 2, 0.5, 0.8)
rrweibull(6, -1, 0.5, 0.8)
p <- (1:9)/10
prweibull(qrweibull(p, -1, 2, 0.8), -1, 2, 0.8)
## [1] 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9

[Package

*evd* version 2.2-4

Index]