A successful call to function `selm`

creates an object of
either of these classes, having a structure described in section
‘Slots’. A set of methods for these classes of objects exist, listed in
section ‘Methods’.

An object can be created by a successful call to function `selm`

.

`call`

:the calling statement.

`family`

:the parametric family of skew-ellitically contoured distributed (SEC) type.

`logL`

:log-likelihood or penalized log-likelihood value achieved at the end of the maximization process.

`method`

:estimation method (

`"MLE"`

or`"MPLE"`

).`param`

:estimated parameters, for various parameterizations.

`param.var`

:approximate variance matrices of the parameter estimates, for various parameterizations.

`size`

:a numeric vector with size of various components.

`fixed.param`

:a vector of parameters which have been kept fixed in the fitting process, if any.

`residuals.dp`

:residual values, for DP-type parameters.

`fitted.values.dp`

:fitted values, for DP-type parameters.

`control`

:a list with control parameters.

`input`

:a list of selected input values.

`opt.method`

:a list with details on the optimization method.

`coef` | `signature(object = "selm")` : ... |

`logLik` | `signature(object = "selm")` : ... |

`plot` | `signature(x = "selm")` : ... |

`show` | `signature(object = "selm")` : ... |

`summary` | `signature(object = "selm")` : ... |

`residuals` | `signature(object = "selm")` : ... |

`fitted` | `signature(object = "selm")` : ... |

`vcov` | `signature(object = "selm")` : ... |

`weights` | `signature(object = "selm")` : ... |

`profile` | `signature(fitted = "selm")` : ... |

`confint` | `signature(object = "selm")` : ... |

`predict` | `signature(object = "selm")` : ... |

`coef` | `signature(object = "mselm")` : ... |

`logLik` | `signature(object = "mselm")` : ... |

`plot` | `signature(x = "mselm")` : ... |

`show` | `signature(object = "mselm")` : ... |

`summary` | `signature(object = "mselm")` : ... |

`residuals` | `signature(object = "mselm")` : ... |

`fitted` | `signature(object = "mselm")` : ... |

`vcov` | `signature(object = "mselm")` : ... |

`weights` | `signature(object = "mselm")` : ... |

See `dp2cp`

for a description of possible parameter sets.
When `logLik`

is used on an object obtained using the MPLE estimation
method, the value reported is actually the *penalized* log-likelihood.

Adelchi Azzalini

See also
`selm`

function, `plot.selm`

,
`summary.selm`

, `dp2cp`

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | ```
data(ais)
m1 <- selm(log(Fe) ~ BMI + LBM, family="SN", data=ais)
summary(m1)
plot(m1)
logLik(m1)
res <- residuals(m1)
fv <- fitted(m1)
#
data(wines, package="sn")
m2 <- selm(alcohol ~ malic + phenols, data=wines)
#
m12 <- selm(cbind(acidity, alcohol) ~ phenols + wine, family="SN", data=wines)
coef(m12)
cp <- coef(m12, vector=FALSE)
dp <- coef(m12, "DP", vector=FALSE)
plot(m12)
plot(m12, which=2, col="gray60", pch=20)
``` |

Questions? Problems? Suggestions? Tweet to @rdrrHQ or email at ian@mutexlabs.com.

Please suggest features or report bugs with the GitHub issue tracker.

All documentation is copyright its authors; we didn't write any of that.