aov.genyates(formula, data=<<see below>>, onedf=F)
Error
term,
nor may it have a multiple response.
data
is omitted, the current search list is used; frequently,
a data frame will have been attached.
onedf==TRUE
, the function returns single
degree of freedom projections, otherwise, projections are collapsed.
aov
.
In addition, the fit contains the projection matrix:
This function produces a more direct computation of an analysis of
variance model than does
aov
.
The
aov.genyates
function will be faster than the
aov
function for
large balanced datasets; for small datasets there is virtually no difference
in speed.
The
proj
component is identical to the result of the
proj.lm
function
applied to the
aov
structure. Thus the two expressions:
proj.lm(aov(formula, data, qr=T, onedf=F))
aov.genyates(formula, data, onedf=F)$proj
yield the same result.
When
onedf
is
TRUE
, there is one projection for each degree of freedom
in the model.
When
onedf==FALSE
, the function
collapses the single degree of freedom projections into multi-degree of freedom
projections. Each column of the collapsed result represents one term of the
analysis of variance table. The sum of squares of each column is the sum of
squares for the corresponding term in the model.
aov.genyates
does no checking for balance (and in fact will erroneously
print that effects are balanced when they are not).
It is up to the user to make sure that the design is balanced.
aov.genyates(Yield ~ Temp * Conc * Cat, catalyst)