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Use this tag for any use of optimization within statistics.

1 vote
1 answer
76 views

How can I make this biological relation into a glm model?

I have a biological relation: Y/m = (X * b) / (1 + X * b) where Y and X are variables, m and b are parameters. m is greater than Y, and everything is greater than 0. I have some training data with …
Count Zero's user avatar
  • 1,029
9 votes
2 answers
2k views

Why does adding L1 penalty to R's optim slows things down so much (relative to no penalty or...

A quick Google search turned up a package call "lbfgs" which "finds the optimum of an objective plus the L1 norm of the problem’s parameters" with "a fast and memory-efficient implementation of these optimization
Count Zero's user avatar
  • 1,029
2 votes
0 answers
219 views

When is logistic regression minimizing under squared error loss the same as maximizing binom... [duplicate]

Implementing logistic regression and getting different results depending on whether I minimize squared error or maximize log likelihood. When are the two equivalent?
Count Zero's user avatar
  • 1,029
1 vote
1 answer
523 views

Neural networks: how can convex optimization produce different weights each time?

However the optimization function (sum squared error in my case) is convex, which means there is one global minima. So I suppose this minima has several equivalent sets of weights that map to it. …
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