# Generating Function for Linear Regression Family with Unknown Scale

### Description

Generates an object of class `"L2RegTypeFamily"`

which represents a linear regression family with standard
normal distributed errors and random regressor where the
scale of the error distribution is unknown.

### Usage

1 2 | ```
NormLinRegScaleFamily(theta, scale = 1, trafo, RegDistr = Norm(),
RegSymm, Reg2Mom, nuisance = FALSE)
``` |

### Arguments

`theta` |
linear regression parameter |

`scale` |
scale parameter for error distribution |

`trafo` |
matrix: transformation of the parameter |

`RegDistr` |
regressor distribution |

`RegSymm` |
symmetry of the regressor distribution |

`Reg2Mom` |
second moment matrix of regressor |

`nuisance` |
logical: is scale nuisance parameter |

### Details

In case `theta`

is missing, it is set to 0.
If `Reg2Mom`

is missing, it is computed via `E`

.

### Value

Object of class `"L2RegTypeFamily"`

### Author(s)

Matthias Kohl Matthias.Kohl@stamats.de

### References

Kohl, M. (2005) *Numerical Contributions to the
Asymptotic Theory of Robustness*. Bayreuth: Dissertation.

### See Also

`L2RegTypeFamily-class`

### Examples

1 2 3 4 | ```
(LM1 <- NormLinRegScaleFamily(Reg2Mom = matrix(1)))
Map(L2deriv(LM1)[[1]])
FisherInfo(LM1)
checkL2deriv(LM1)
``` |

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