The class is returned by calling the function `cgarchfilter`

.

`mfilter`

:Object of class

`"vector"`

Multivariate filter list.`model`

:Object of class

`"vector"`

Model specification list.

Class `"'>mGARCHfilter"`

, directly.
Class `"'>GARCHfilter"`

, by class "mGARCHfilter", distance 2.
Class `"'>rGARCH"`

, by class "mGARCHfilter", distance 3.

- coef
`signature(object = "cGARCHfilter")`

: The coefficient vector (see note).- fitted
`signature(object = "cGARCHfilter")`

: The conditional mean filtered data (xts object).- likelihood
`signature(object = "cGARCHfilter")`

: The joint likelihood.- rcor
`signature(object = "cGARCHfilter")`

: The conditional correlation array with third dimension labels the time index.- rcov
`signature(object = "cGARCHfilter")`

: The conditional covariance array with third dimension labels the time index.- residuals
`signature(object = "cGARCHfilter")`

: The model residuals (xts object).- show
`signature(object = "cGARCHfilter")`

: Summary.- sigma
`signature(object = "cGARCHfilter")`

: The model conditional sigma (xts object).- rshape
`signature(object = "cGARCHfilter")`

: The multivariate distribution shape parameter(s).- rskew
`signature(object = "cGARCHfilter")`

: The multivariate distribution skew parameter(s).

Joe, H. *Multivariate Models and Dependence Concepts*, 1997,
Chapman \& Hall, London.
Genest, C., Ghoudi, K. and Rivest, L. *A semiparametric estimation
procedure of dependence parameters in multivariate families of distributions*,
1995, Biometrika, 82, 543-552.