twoway.formula(formula=formula(data), data=sys.parent(), subset, na.action, trim=.5, iter=6, eps=<<see below>>, print=F)
z ~ x * y
The
z
variable is a numeric response.
Missing values (
NA
s) are allowed.
The
x
represents the row variable.
The
y
represents the column variable.
formula
.
model.frame
after
any
subset
argument has been used.
The default (with
na.fail
) is to create an error
if any missing values are found.
A possible alternative is
na.omit
, which deletes observations
that contain one or more missing values.
trim=0
will cause
analysis by means, .25 by midmeans, etc.
eps
is given, the algorithm will
iterate until the maximum change in row or column effects is
less than
eps
. The default is to iterate until the specified number
of iterations or until converged to the accuracy of the
machine arithmetic. It is not always possible to converge
to a unique answer.
TRUE
, the maximum change in row/column effects in
the last iteration is printed.
resid
,
row
,
col
,
and
grand
, such that
x[i,j]
equals
grand + row[i] + col[j] + resid[i,j]
This is the formula version of
twoway
.
The response
z
is converted to a table (matrix) cross classified
by the values of
x
and
y
.
This matrix is then passed to
twoway.default
.
For further details see the
twoway
documentation.
twoway(coal ~ x * y, data=coal.ash)