Description Usage Arguments Details Value Note Author(s) References See Also Examples

Density, distribution function, quantile function and random generation for the 4-parameter bivariate logistic distribution.

1 2 3 |

`x1, x2, q1, q2` |
vector of quantiles. |

`n` |
number of observations.
Same as |

`loc1, loc2` |
the location parameters |

`scale1, scale2` |
the scale parameters |

`log` |
Logical.
If |

See `bilogis`

, the VGAM family function for
estimating the four parameters by maximum likelihood estimation, for
the formula of the cumulative distribution function and other details.

`dbilogis`

gives the density,
`pbilogis`

gives the distribution function, and
`rbilogis`

generates random deviates (a two-column matrix).

Gumbel (1961) proposed two bivariate logistic distributions with
logistic distribution marginals, which he called Type I and Type II.
The Type I is this one.
The Type II belongs to the Morgenstern type.
The `biamhcop`

distribution has, as a special case,
this distribution, which is when the random variables are independent.

T. W. Yee

Gumbel, E. J. (1961)
Bivariate logistic distributions.
*Journal of the American Statistical Association*,
**56**, 335–349.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 | ```
## Not run: par(mfrow = c(1, 3))
ymat <- rbilogis(n = 2000, loc1 = 5, loc2 = 7, scale2 = exp(1))
myxlim <- c(-2, 15); myylim <- c(-10, 30)
plot(ymat, xlim = myxlim, ylim = myylim)
N <- 100
x1 <- seq(myxlim[1], myxlim[2], len = N)
x2 <- seq(myylim[1], myylim[2], len = N)
ox <- expand.grid(x1, x2)
z <- dbilogis(ox[,1], ox[,2], loc1 = 5, loc2 = 7, scale2 = exp(1))
contour(x1, x2, matrix(z, N, N), main = "density")
z <- pbilogis(ox[,1], ox[,2], loc1 = 5, loc2 = 7, scale2 = exp(1))
contour(x1, x2, matrix(z, N, N), main = "cdf")
## End(Not run)
``` |

VGAM documentation built on May 19, 2017, 10:21 a.m.

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