Description Usage Arguments Details Value Examples
Efficient Generalized Linear Model ("eglm"
) is used to fit generalized
linear models in an equivalent way to "glm"
but in a reduced
time depending on the design matrix and the family (or link).
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formula |
an object of class |
family |
a description of the error distribution and link function to be
used in the model. This can be a character string naming a
family function, a family function or the result of a call to a family
function. See |
data |
an optional data frame, list or environment (or object coercible
by |
weights |
an optional vector of weights to be used in the fitting
process. Should be |
subset |
an optional vector specifying a subset of observations to be used in the fitting process. |
na.action |
a function which indicates what should happen when the data
contain |
start |
starting values for the parameters in the linear predictor. |
etastart |
starting values for the linear predictor. |
mustart |
starting values for the vector of means. |
offset |
this can be used to specify an a priori known component
to be included in the linear predictor during fitting. This should be
|
control |
a list of parameters for controlling the fitting process. For
|
model |
a logical value indicating whether model frame should be included as a component of the returned value. |
method |
the method to be used in fitting the model. The default method
|
x, y |
logical values indicating whether the
model matrix ( |
singular.ok |
logical; if FALSE a singular fit is an error. |
contrasts |
an optional list. See the |
reduce |
logical; if TRUE an alternate design matrix of |
... |
For eglm: arguments to be used to form the default control argument if it is not supplied directly. For weights: further arguments passed to or from other methods. |
Models for eglm
are specified symbolically.
A typical model has the form response ~ terms
where response
is the (numeric) response vector and terms
is a series of terms which
specifies a linear predictor for response
. A terms specification of
the form first + second
indicates all the terms in first
together with all the terms in second
with duplicates removed. A
specification of the form first:second
indicates the set of
terms obtained by taking the interactions of all terms in first
with all terms in second
. The specification first*second
indicates the cross of first
and second
. This is
the same as first + second + first:second
, and exactly the same as
"glm"
from the stats package.
An object of class "eglm" that behaves the same way as the "glm"
class, see the function "glm"
. This output also includes the
logical "reduce" and, depending on it, the reduced design matrix "xtx"
when the reduce argument is set to TRUE.
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