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I have a rather technical question. I'm trying to find the Yule-Nielsen factor n in the equation

enter image description here

https://en.wikipedia.org/wiki/Neugebauer_equations

I've read that n is empirically derived from the "best fit" of the model to the training data: link here

My understanding is that the training data consists of random colour patches and the spectra of each is measured using a spectrophotometer. But how do you build the best-fit model of a collection of spectra? Suppose each spectrum is formulated as a M by one matrix. How do you come up with a best-fit model without knowing the value of n? Is the best-fit an M dimensional plane?

  • I think this is offtopic. Why would you expect designers to know this? – Lucian Jan 12 at 7:38
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    @Lucian I was hoping that some designer ran into a similar situation when calibrating or optimising their prints. – John M. Jan 12 at 8:03
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    They would have to be really passionate to go that far, but ok i guess. – Lucian Jan 12 at 8:24
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    Well yes really passionate and wasteful its easier to just measure and use icc profiles. Its not enoigh to measure once, machines and substrates age so you will keep continue doing this also you need to do it again once you have a batch of paper changed. – joojaa Jan 12 at 10:20
  • I'm curious about what you need this for. It's way beyond anything I ever needed to know doing design and prepress. For a designer preparing images for print this seems like extreme overkill, but maybe you are developing some kind of print method from scratch? – Wolff Jan 13 at 18:04

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