| anova.lmRob {robust} | R Documentation |
Compute an analysis of variance table for one or more robust linear model fits.
## S3 method for class 'lmRob':
anova(object, ..., test = c("RF", "RWald"))
## S3 method for class 'lmRoblist':
anova(object, const, ipsi, yc, test = c("RWald", "RF"), ...)
object |
an lmRob object. |
... |
additional arguments required by the generic anova function. If ... contains additional robustly fitted linear models then the function anova.lmRoblist is dispatched. |
const |
a numeric value containing the tuning constant computed by lmRob.const. |
ipsi |
an integer value specifying the psi-function. |
yc |
a numeric value containing the tuning constant computed by lmRob.effvy. |
test |
a single character value specifying which test should be computed in the Anova table. The possible choices are "RWald" and "RF". |
The default test used by anova is the "RWald" test, which is the Wald test based on robust estimates of the coefficients and covariance matrix. If test is "RF", the robustified F-test is used instead.
an anova object.
Hampel, F. R., Ronchetti, E. M., Rousseeuw, P. J., and Stahel, W. A. (1986). Robust statistics: the approach based on influence functions. John Wiley & Sons.
data(stack.dat) stack.small <- lmRob(Loss ~ Water.Temp + Acid.Conc., data = stack.dat) stack.full <- lmRob(Loss ~ ., data = stack.dat) anova(stack.full) anova(stack.full, stack.small)