Rolf Turner
2017-Dec-11 18:15 UTC
[R] OT -- isotonic regression subject to bound constraints.
Well, I could argue that it's not *completely* OT since my question is motivated by an enquiry that I received in respect of a CRAN package "Iso" that I wrote and maintain. The question is this: Given observations y_1, ..., y_n, what is the solution to the problem: minimise \sum_{i=1}^n (y_i - y_i^*)^2 with respect to y_1^*, ..., y_n^* subject to the "isotonic" constraint y_1^* <= y_2^* <= ... <= y_n^* and the *additional8 bound constraint a <= y_1^* and y_n^* <= b, where a and b are given constants? I have googled around a bit (unsuccessfully) and have asked this question on crossvalidated a couple of days ago, with no response whatever. So I thought that I might try the super-knowledgeable R community, in the hope that someone out there might be able to tell me something useful. Note that the question can be expressed as finding the projection of the point (y_1, ..., y_n) onto the intersection of the isotonic cone and the hypercube [a,b]^n. At first I thought that protecting onto the isotonic cone and then projection that result onto the hypercube might work, but I am now pretty sure that is hopelessly naive. Any hints? Ta. cheers, Rolf Turner -- Technical Editor ANZJS Department of Statistics University of Auckland Phone: +64-9-373-7599 ext. 88276
Rolf Turner
2017-Dec-11 18:23 UTC
[R] OT -- isotonic regression subject to bound constraints.
On 12/12/17 07:15, Rolf Turner wrote:> > Well, I could argue that it's not *completely* OT since my question is > motivated by an enquiry that I received in respect of a CRAN package > "Iso" that I wrote and maintain. > > The question is this:? Given observations y_1, ..., y_n, what is the > solution to the problem: > > ? minimise \sum_{i=1}^n (y_i - y_i^*)^2 > > with respect to y_1^*, ..., y_n^* subject to the "isotonic" constraint > y_1^* <= y_2^* <= ... <= y_n^* and the *additional8 bound constraint > a <= y_1^* and y_n^* <= b, where a and b are given constants?<SNIP> Scrub that question! *Just* after I sent it (wouldn't you know!) I got an email from my original enquirer telling me that he'd found the solution in the package OrdMonReg on CRAN. Sorry for the noise. cheers, Rolf Turner -- Technical Editor ANZJS Department of Statistics University of Auckland Phone: +64-9-373-7599 ext. 88276