Compute an Anova Object by Dropping Terms

DESCRIPTION:

drop1.lmRob is used to investigate a robust Linear Model object by recomputing it, successively omitting each of a number of specified terms.

USAGE:

drop1.lmRob(object, scope, scale, keep, fast = F, ...) 

REQUIRED ARGUMENTS:

object
an lmRob object.

OPTIONAL ARGUMENTS:

scope
an optional formula object describing the terms to be dropped. Typically this argument is omitted, in which case all possible terms are dropped (without breaking hierarchy rules). The scope can also be a character vector of term labels. If the argument is supplied as a formula, any "." is interpreted relative to the formula implied by the object argument.
scale
an estimate of the scale of the residuals. If not supplied, the initial estimate of the scale in object is used.
keep
a character vector of names of components that should be saved for each subset model. Only names from the set "coefficients", "fitted" and "residuals" are allowed. If keep is TRUE, the complete set is saved. The default behavior is not to keep anything.
fast
if TRUE the robust initial estimate (used when fitting each of the reduced models) is replaced by a weighted least squares estimate using the robust weights stored in object.

VALUE:

An anova object is constructed, consisting of the term labels, the degrees of freedom, and Robust Final Prediction Errors (RFPE) for each subset model. If keep is missing, this is what is returned. If keep is present, a list with components "anova" and "keep" is returned. In this case, the "keep" component is a matrix of mode "list", with a column for each subset model, and a row for each component kept.

DETAILS:

This function is a method for the generic function drop1 for class "lmRob" . It can be invoked by calling drop1 for an object of the appropriate class, or directly by calling drop1.lmRob regardless of the class of the object.

SEE ALSO:

, , , .

EXAMPLES:

stack.df <- data.frame(Loss=stack.loss,stack.x) 
stack.rob <- lmRob(Loss~Air.Flow+Water.Temp+Acid.Conc.,data=stack.df, 
                   robust.control=lmRob.robust.control(final="MM")) 
drop1(stack.rob)