Hi,
I am solving a projection pursuit regression problem, of the
form y = \sum_i f_i (a_i^T x), where a_i are unknown directions, while
f_i are unknown univariate link functions. The following is known about
each f_i:
1. f_i (0) = 0 (that is, each f_i passes through the origin)
2. f_i is monotonic.
Is there a way to ensure that the function ppr() in R produces solutions that
respect the above two conditions on f_i?
Also, are there ways to enforce constraints on the a_i, say, that the first
component is positive?
Or that one of the a_i is known.
Thanks!
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