avas(x, y, wt=<<see below>>, monotone=NULL, linear=NULL, categorical=NULL, circular=NULL, tolerance=0.01, span.var="cv")
x
.
Missing values are not accepted.
wt
should be the same as the length of
y
.
By default an unweighted regression is carried out (all weights are unity).
monotone
refer to the columns of the
x
matrix.
linear
refer to columns of the
x
matrix and a zero
value refers to the
y
variable.
categorical
refer to columns of the
x
matrix.
circular
refer to columns of the
x
matrix.
A variable specified as
circular
that has values outside the range [0, 1]
will be transformed using the default (general ordered) transformation.
tolerance
in 3 consecutive iterations.
span.var
must lie between
0
and
1
,
or can be set to the character string
"cv"
for cross validation.
x
values.
This is a vector when there is only one x variable.
y
of the transformed
y
values.
The
y
variable can only be transformed using the
linear
or
general ordered (the default) transformations.
Tibshirani, R. (1988).
Estimating transformations for regression via additivity
and variance stabilization.
Journal of the American Statistical Association
83, 394-405.
The chapter "Regression and Smoothing for Continous Response Data" in the S-PLUS Guide to Statistical and Mathematical Analysis.
x <- runif(200, 0, 2*pi); y <- exp(sin(x)+rnorm(200)/2) a <- avas(x, y) plot(y, a$ty) # view the response transformation plot(x, a$tx) # view the carrier transformation plot(a$tx, a$ty) # examine the linearity of the fitted model