mle.cp {wle} | R Documentation |
The Mallows Cp is evaluated for each submodel.
mle.cp(formula, data=list(), model=TRUE, x=FALSE, y=FALSE, var.full=0, contrasts=NULL)
formula |
a symbolic description of the model to be fit. The details of model specification are given below. |
data |
an optional data frame containing the variables
in the model. By default the variables are taken from
the environment which mle.cp is called from. |
model, x, y |
logicals. If TRUE the corresponding components of the fit (the model frame, the model matrix, the
response). |
var.full |
the value of variance to be used in the denominator of the Mallows Cp, if 0 the variance estimated from the full model is used. |
contrasts |
an optional list. See the contrasts.arg
of model.matrix.default . |
Models for mle.cp
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 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
.
mle.cp
returns an object of class
"mle.cp"
.
The function summary
is used to obtain and print a summary of the results, only models below the bisector are reported.
The generic accessor functions coefficients
and residuals
extract coefficients and residuals returned by mle.cp
.
The object returned by mle.cp
are:
cp |
Mallows Cp for each submodels |
coefficients |
the parameters estimator, one row vector for eac submodel. |
scale |
an estimation of the error scale, one value for each submodel. |
residuals |
the residuals from the estimated model, one column vector for each submodel. |
call |
the match.call(). |
contrasts |
|
xlevels |
|
terms |
the model frame. |
model |
if model=TRUE a matrix with first column the dependent variable and the remain column the explanatory variables for the full model. |
x |
if x=TRUE a matrix with the explanatory variables for the full model. |
y |
if y=TRUE a vector with the dependent variable. |
info |
not well working yet, if 0 no error occurred. |
Claudio Agostinelli
library(wle) data(hald) cor(hald) result <- mle.cp(y.hald~x.hald) summary(result) plot(result)