Regression Diagnostics
Usage
lm.influence(lm.obj)
Arguments
lm.obj
|
an object as returned by lm.
|
Description
This function provides the basic quantities which are
used in forming a wide variety of diagnostics for
checking the quality of regression fits.
The functions listed below give a more direct way
of computing a variety of regression diagnostics.
Value
A list containing the following components:
hat
|
a vector containing the diagonal of the ``hat'' matrix.
|
coefficients
|
the change in the estimated coefficients which results
when the i-th case is dropped from the regression is contained in
the i-th row of this matrix.
|
sigma
|
a vector whose i-th element contains the estimate
of the residual standard deviation obtained when the i-th
case is dropped from the regression.
|
Note
The coefficients returned by the R version
of lm.influence differ from those computed by S.
Rather than returning the coefficients which result
from dropping each case, we return the changes in the coefficients.
This is more directly useful in many diagnostic measures.References
Belsley, D. A., E. Kuh and R. E. Welsch (1980).
Regression Diagnostics.
New York: Wiley.See Also
summary.lm for summary and related methods;
influence.measures,
hat for the hat matrix diagonals,
dfbetas,
dffits,
covratio,
cooks.distance,
lm.Examples
# Analysis of the life-cycle savings data
# given in Belsley, Kuh and Welsch.
data(savings)
summary(lm.SR <- lm(sr ~ pop15 + pop75 + dpi + ddpi, data=savings),corr= TRUE)
rstudent(lm.SR)
dfbetas(lm.SR)
dffits(lm.SR)
covratio(lm.SR)