get_start {glmnet} | R Documentation |

## Get null deviance, starting mu and lambda max

### Description

Return the null deviance, starting mu and lambda max values for initialization. For internal use only.

### Usage

```
get_start(
x,
y,
weights,
family,
intercept,
is.offset,
offset,
exclude,
vp,
alpha
)
```

### Arguments

`x` |
Input matrix, of dimension |

`y` |
Quantitative response variable. |

`weights` |
Observation weights. |

`family` |
A description of the error distribution and link function to be
used in the model. This is the result of a call to a family function.
(See |

`intercept` |
Does the model we are fitting have an intercept term or not? |

`is.offset` |
Is the model being fit with an offset or not? |

`offset` |
Offset for the model. If |

`exclude` |
Indices of variables to be excluded from the model. |

`vp` |
Separate penalty factors can be applied to each coefficient. |

`alpha` |
The elasticnet mixing parameter, with |

### Details

This function is called by `glmnet.path`

for null deviance, starting mu
and lambda max values. It is also called by `glmnet.fit`

when used
without warmstart, but they only use the null deviance and starting mu values.

When `x`

is not sparse, it is expected to already by centered and scaled.
When `x`

is sparse, the function will get its attributes `xm`

and
`xs`

for its centering and scaling factors.

Note that whether `x`

is centered & scaled or not, the values of `mu`

and `nulldev`

don't change. However, the value of `lambda_max`

does
change, and we need `xm`

and `xs`

to get the correct value.

*glmnet*version 4.1-8 Index]