Alternating conditional expectations: Difference between revisions

Revision as of 02:27, 18 June 2018

Revision as of 02:37, 18 June 2018

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In the bivariate case, ACE algorithm can also be regarded as a method for estimating the maximal correlation between two variables.

==Software Implementation==

The ACE algorithm was developed in the context of known distributions. In practice, data distributions are seldom known and the conditional expectation

should be estimated from data. [[R language]] has a package <kbd>acepack</kbd> which implements ACE algorithm. The following example shows its usage:

TWOPI <- 8*atan(1)

x <- runif(200,0,TWOPI)

y <- exp(sin(x)+rnorm(200)/2)

a <- ace(x,y)

par(mfrow=c(3,1))

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

== References ==