Alternating conditional expectations: Difference between revisions

Revision as of 16:28, 2 June 2022

Revision as of 11:41, 11 July 2022

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== 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:

<syntaxhighlight lang="r">

library(acepack)

TWOPI <- 8 * atan(1)

xTWOPI <- runif(200,8 0,* TWOPIatan(1)

yx <- exprunif(sin(x)200, +0, rnorm(200)/2TWOPI)

ay <- aceexp(sin(x,) y+ rnorm(200)/2)

a <- ace(x, y)

par(mfrow=c(3,1))

plot(a$y, a$ty) # view the response transformation

plot(a$xy, a$txty) # view the carrierresponse transformation

plot(a$txx, a$tytx) # examine the linearity ofview the fittedcarrier modeltransformation

plot(a$tx, a$ty) # examine the linearity of the fitted model

</syntaxhighlight>

== Discussion ==