| logtrans(MASS) | R Documentation |
Find and optionally plot the marginal likelihood for alpha
for a transformation model of the form log(y + alpha) ~ x1 + x2 + ...{}.
logtrans(object, ..., alpha = seq(0.5, 6, by = 0.25) - min(y),
plotit = <<see below>>, interp = <<see below>>,
xlab="alpha", ylab="log Likelihood")
object |
Fitted linear model object, or formula defining the untransformed
model that is y ~ x1 + x2 + ...{}. The function is generic.
|
... |
If object is a formula, this argument may specify a data frame
as for lm.
|
alpha |
Set of values for the transformation parameter, alpha. |
plotit |
Should plotting be done? (Default is TRUE if a non-null device is
currently active, else FALSE.)
|
interp |
Should the marginal log-likelihood be interpolated with a spline
approximation? (Default is TRUE if plotting is to be done and
the number of real points is less than 100.)
|
xlab |
as for plot.
|
ylab |
as for plot.
|
List with components x (for alpha) and y (for the marginal
log-likelihood values).
A plot of the marginal log-likelihood is produced, if requested, together with an approximate mle and 95% confidence interval.
Venables & Ripley, Chapter 6.
data(quine)
logtrans(Days ~ Age*Sex*Eth*Lrn, data = quine,
alpha = seq(0.75, 6.5, len=20), singular.ok = TRUE)