TITLE(ace @@ ace: Alternating Conditional Expectations )
USAGE(
ace(x, y, wt, mon, lin, cat, circ, delrsq)

)
ARGUMENTS(
ARG(x@@)
a matrix containing the independent variables.
ARG(y@@)
a vector containing the response variable.
ARG(wt@@)
an optional vector of weights.
ARG(mon@@)
an optional integer vector specifying which variables are to be
transformed by monotone transformations.
Positive values in LANG(mon) refer to columns of the LANG(x) matrix and zero
to the response variable.
ARG(lin@@)
an optional integer vector specifying which variables are to be
transformed by linear transformations.
Positive values in LANG(lin) refer to columns of the LANG(x) matrix and zero
to the response variable.
ARG(cat@@)
an optional integer vector specifying which variables assume
categorical values.
Positive values in LANG(cat) refer to columns of the LANG(x)
matrix and zero to the response variable.
ARG(circ@@)
an integer vector specifying which variables assume
circular (periodic) values.
Positive values in LANG(circ) refer to columns of the LANG(x)
matrix and zero to the response variable.
ARG(delrsq@@)
termination threshold.  Iteration stops when R-squared
changes by less than LANG(delrsq) in 3 consecutive iterations
(default 0.01).
)
PARA BOLD(VALUE)
structure with the following components:
ARG(x@@)
the input x matrix.
ARG(y@@)
the input y vector.
ARG(tx@@)
the transformed x values.
ARG(ty@@)
the transformed y values.
ARG(rsq@@)
the multiple R-squared value for the transformed values.
ARG(l@@)
not used in this version of ace
ARG(m@@)
not used in this version of ace

PARA BOLD(DESCRIPTION )
Uses the alternating conditional expectations algorithm to find the transformations of y and x that maximise the proportion of variation in y explained by x. 

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PARA BOLD(REFERENCE)
 Breiman and Friedman, Journal of the American Statistical Association (September, 1985)
The R code is adapted from S code for avas() by Tibshirani, in the Statlib S archive; the FORTRAN is a double-precision version of FORTRAN code by Friedman and Spector in the Statlib general archive.


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EXAMPLES(
TWOPI <- 8*atan(1)
x <- runif(200,0,TWOPI)
y <- exp(sin(x)+rnorm(200)/2)
a <- avas(x,y)
plot(a\$y,a\$ty)  # view the response transformation
plot(a\$x,a\$tx)  # view the carrier transformation
plot(a\$tx,a\$ty) # examine the linearity of the fitted model
)













