# family.elliptical: Family Objects for Elliptical Models In gwer: Geographically Weighted Elliptical Regression

## Description

The family object provide an specify details of the model used by functions such as `elliptical`, `gwer` and `gwer.multiscale`. The distribution functions are necessary to specify the random component of the regression models with elliptical errors.

## Usage

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20``` ```## S3 method for class 'elliptical' family(object, ...) Normal() Cauchy() LogisI() LogisII() Student(df = stop("no df argument")) Powerexp(k = stop("no k argument")) Glogis(parma = stop("no alpha=alpha(m) or m argument")) Gstudent(parm = stop("no s or r argument")) Cnormal(parmt = stop("no epsi or sigma argument")) ```

## Arguments

 `object` an object with the result of the fitted elliptical regression model. `...` arguments to be used to form the default control argument if it is not supplied directly. `df` degrees of freedom. `k` shape parameter. `parma` parameter vector (alpha, m). `parm` parameter vector (s, r) for this distribuition. `parmt` parameters vector (epsi, sigma).

## Value

An object of class “family” specifying a list with the follows elements:

 `family` character: the family name. `g0, g1, g2, g3, g4, g5` derived fuctions associated with the distribution family defined. `df` degree of freedom for t-Student distribution. `s, r` shape parameters for generalized t-Student distribution. `alpha` shape parameter for contaminated normal and generalized logistic distributions. `mp` shape parameter for generalized logistic distribution. `epsi,sigmap` dispersion parameters for contaminated normal distribution. `k` shape parameter for power exponential distribution.

## References

Fang, K. T., Kotz, S. and NG, K. W. (1990, ISBN:9781315897943). Symmetric Multivariate and Related Distributions. London: Chapman and Hall.

`elliptical`, `gwer`
 ```1 2 3 4 5 6 7 8 9``` ```data(luzdat) y <- luzdat\$y x1 <- luzdat\$x1 ; x1 <- factor(x1) ; x1 <- C(x1,treatment) x2 <- luzdat\$x2 x3 <- (luzdat\$x2)^2 luz <- data.frame(y,x1,x2,x3) elliptical.fitt <- elliptical(y ~ x1+x2+x3, family = Normal() ,data=luz) family(elliptical.fitt) ```