Summarizing Robust Linear Model Fits
Compute a summary of the robustly fitted linear model.
## S3 method for class 'lmRob' summary(object, correlation = FALSE, bootstrap.se = FALSE, ...)
object |
an lmRob object. |
correlation |
a logical value. If |
bootstrap.se |
a logical value. If |
... |
additional arguments required by the generic |
The summary is returned in a list of class summary.lmRob and contains the following components:
sigma |
a single numeric value containing the residual scale estimate. |
df |
a numeric vector of length 3 containing integer values: the rank of the model matrix, the residual degrees of freedom, and the number of coefficients in the model. |
cov.unscaled |
the unscaled covariance matrix; i.e, the matrix that, when multiplied by the estimate of the error variance, yields the estimated covariance matrix for the coefficients. |
correlation |
the correlation coefficient matrix for the coefficients in the model. |
... |
the remaining components are the same as the corresponding components in an |
data(stack.dat) stack.rob <- lmRob(Loss ~ ., data = stack.dat) stack.sum <- summary(stack.rob) stack.sum stack.bse <- summary(stack.rob, bootstrap.se = TRUE) stack.bse
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