lm.influence {base} | R Documentation |
lm.influence(lm.obj)
lm.obj |
an object as returned by lm . |
The functions listed in See Also give a more direct way of computing a variety of regression diagnostics.
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. |
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.
Note that cases with weights == 0
are dropped (contrary
to the situation in S).
Belsley, D. A., Kuh, E. and Welsch, R. E. (1980) Regression Diagnostics. New York: Wiley.
summary.lm
for summary
and related methods;
influence.measures
,
hat
for the hat matrix diagonals,
dfbetas
,
dffits
,
covratio
,
cooks.distance
,
lm
.
## Analysis of the life-cycle savings data given in Belsley, Kuh ## and Welsch. data(LifeCycleSavings) summary(lm.SR <- lm(sr ~ pop15 + pop75 + dpi + ddpi, data = LifeCycleSavings), corr = TRUE) rstudent(lm.SR) dfbetas(lm.SR) dffits(lm.SR) covratio(lm.SR)