get_start {glmnet} | R Documentation |
Return the null deviance, starting mu and lambda max values for initialization. For internal use only.
get_start(
x,
y,
weights,
family,
intercept,
is.offset,
offset,
exclude,
vp,
alpha
)
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 |
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.