# transform-extract-methods: Linear transformation and extraction of generalized... In ghyp: A package on the generalized hyperbolic distribution and its special cases

## Description

The `transform` function can be used to linearly transform generalized hyperbolic distribution objects (see Details). The extraction operator `[` extracts some margins of a multivariate generalized hyperbolic distribution object.

## Usage

 ```1 2 3 4 5``` ```## S4 method for signature 'ghyp' transform(`_data`, summand, multiplier) ## S3 method for class 'ghyp' x[i = c(1, 2)] ```

## Arguments

 `_data` An object inheriting from class `ghyp`. `summand` A `vector`. `multiplier` A `vector` or a `matrix`. `x` A multivariate generalized hyperbolic distribution inheriting from class `ghyp`. `i` Index specifying which dimensions to extract. `...` Arguments passed to `transform`.

## Details

If X is GH distributed, `transform` gives the distribution object of “multiplier * X + summand”, where X is the argument named `_data`.

If the object is of class `mle.ghyp`, iformation concerning the fitting procedure (cf. `ghyp.fit.info`) will be lost as the return value is an object of class `ghyp`.

## Value

An object of class `ghyp`.

## Author(s)

David Luethi

`scale`, `ghyp`, `fit.ghypuv` and `fit.ghypmv` for constructors of `ghyp` objects.
 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15``` ``` ## Mutivariate generalized hyperbolic distribution multivariate.ghyp <- ghyp(sigma=var(matrix(rnorm(9),ncol=3)), mu=1:3, gamma=-2:0) ## Dimension reduces to 2 transform(multivariate.ghyp, multiplier=matrix(1:6,nrow=2), summand=10:11) ## Dimension reduces to 1 transform(multivariate.ghyp, multiplier=1:3) ## Simple transformation transform(multivariate.ghyp, summand=100:102) ## Extract some dimension multivariate.ghyp[1] multivariate.ghyp[c(1, 3)] ```