The summary.lm
method is applied to each lm
component of
object
to produce summary information on the individual fits,
which is organized into a list of summary statistics. The returned
object is suitable for printing with the print.summary.lmList
method.
# S3 method for lmList
summary(object, pool, …)
an object inheriting from class "lmList"
, representing
a list of lm
fitted objects.
an optional logical value indicating whether a pooled
estimate of the residual standard error should be used. Default is
attr(object, "pool")
.
some methods for this generic require additional arguments. None are used in this method.
a list with summary statistics obtained by applying summary.lm
to the elements of object
, inheriting from class
summary.lmList
. The components of value
are:
a list containing an image of the lmList
call that
produced object
.
a three dimensional array with summary information
on the lm
coefficients. The first dimension corresponds to
the names of the object
components, the second dimension is
given by "Value"
, "Std. Error"
, "t value"
,
and "Pr(>|t|)"
, corresponding, respectively, to the
coefficient estimates and their associated standard errors,
t-values, and p-values. The third dimension is given by the
coefficients names.
a three dimensional array with the
correlations between the individual lm
coefficient
estimates. The first dimension corresponds to the names of the
object
components. The third dimension is given by the
coefficients names. For each coefficient, the rows of the associated
array give the correlations between that coefficient and the
remaining coefficients, by lm
component.
a three dimensional array with the unscaled
variances/covariances for the individual lm
coefficient
estimates (giving the estimated variance/covariance for the
coefficients, when multiplied by the estimated residual errors). The
first dimension corresponds to the names of the object
components. The third dimension is given by the
coefficients names. For each coefficient, the rows of the associated
array give the unscaled covariances between that coefficient and the
remaining coefficients, by lm
component.
an array with the number of degrees of freedom for the model
and for residuals, for each lm
component.
the total number of degrees of freedom for
residuals, corresponding to the sum of residuals df of all lm
components.
an array with the F test statistics and
corresponding degrees of freedom, for each lm
component.
the value of the pool
argument to the function.
a vector with the multiple R-squared statistics for
each lm
component.
a list with components given by the residuals from
individual lm
fits.
the pooled estimate of the residual standard error.
a vector with the residual standard error estimates for
the individual lm
fits.
the terms object used in fitting the individual lm
components.
# NOT RUN {
fm1 <- lmList(distance ~ age | Subject, Orthodont)
summary(fm1)
# }
Run the code above in your browser using DataLab