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.
USAGE:
summary(object, pool)
REQUIRED ARGUMENTS:
object
an object inheriting from class
lmList, representing
a list of
lm fitted objects.
OPTIONAL ARGUMENTS:
pool
an optional logical value indicating whether a pooled
estimate of the residual standard error should be used. Default is
attr(object, "pool").
VALUE:
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:
call
a list containing an image of the
lmList call that
produced
object.
coefficients
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.
correlation
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.
cov.unscaled
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.
df
an array with the number of degrees of freedom for the model
and for residuals, for each
lm component.
df.residual
the total number of degrees of freedom for
residuals, corresponding to the sum of residuals df of all
lm
components.
fstatistics
an array with the F test statistics and
corresponding degrees of freedom, for each
lm component.
pool
the value of the
pool argument to the function.
r.squared
a vector with the multiple R-squared statistics for
each
lm component.
residuals
a list with components given by the residuals from
individual
lm fits.
RSE
the pooled estimate of the residual standard error.
sigma
a vector with the residual standard error estimates for
the individual
lm fits.
terms
the terms object used in fitting the individual
lm
components.
SEE ALSO:
,
EXAMPLES:
fm1 <- lmList(distance ~ age | Subject, Orthodont)
summary(fm1)