Hi Rui,
I was not aware of this function, however it looks like it should work for
me. Many thanks for this intuition.
However, in my optimization there are 3 constraints as below,
1) sum of all parameters should be 1
2) all parameters should be positive
3) last parameter should be greater than
Às 13:59 de 28/03/2025, Daniel Lobo escreveu:
Hi Duncan,
Thanks for your comment, I agree with that.
But, how it can be justified that an Optimizer gives a result which is
inferior to the starting value? At most, resulting value can remain at the
same level, isnt it?
On Fri, 28 Mar 2025 at 14:
That's a question for the maintainer of the package you used.
Duncan Murdoch
On 2025-03-28 9:59 a.m., Daniel Lobo wrote:
Hi Duncan,
Thanks for your comment, I agree with that.
But, how it can be justified that an Optimizer gives a result which is
inferior to the starting value? At most, resu
Every time I give a seminar on optimization (most recently in Feb
at Univ Cote d'Azur -- thank you Yassine for the welcome!) I point out
Algorithms CONVERGE
Programs TERMINATE
If you race a Maserati (fmincon?) on a dirt bike course, you'll likely
get stuck on the first mud mound, which co
Hi Duncan,
Thanks for your comment, I agree with that.
But, how it can be justified that an Optimizer gives a result which is
inferior to the starting value? At most, resulting value can remain at the
same level, isnt it?
On Fri, 28 Mar 2025 at 14:34, Duncan Murdoch
wrote:
> I haven't run your
I haven't run your code, but since Kendall correlation is based on
ranks, your Fn is probably locally constant with jumps when the ranks
change. That's a really hard kind of function to maximize, and the
algorithm used by fmincon is not appropriate to do it.
Sorry, but I don't know if there i
The objective is to MAXIMIZE the Kendall Correlation.
Given that ?pracma::fmincon minimizes the function, I added a negative sign
in the objective function.
Description
Find minimum of multivariable functions with nonlinear constraints.
Therefore we should not remove the negative sign.
On Fri,
Às 19:36 de 27/03/2025, Daniel Lobo escreveu:
My code is to minimize the objective function
therefore, shouldnt I expect that
StartingValue = c(0.12, 0.04, 0.07, 0.03, 0.06, 0.07, 0.07, 0.04, 0.09,
0.08, 0.02, 0.02, 0.03, 0.06, 0.02, 0, 0.07, 0.05, 0.02, 0.02, 0.02)
Fn(q1$par) < Fn(StartingValu
My code is to minimize the objective function
therefore, shouldnt I expect that
StartingValue = c(0.12, 0.04, 0.07, 0.03, 0.06, 0.07, 0.07, 0.04, 0.09,
0.08, 0.02, 0.02, 0.03, 0.06, 0.02, 0, 0.07, 0.05, 0.02, 0.02, 0.02)
Fn(q1$par) < Fn(StartingValue)
## FALSE
Below is the corrected code that ca
Às 18:35 de 27/03/2025, Daniel Lobo escreveu:
Hi,
I have below minimization problem
MyDat = structure(list(c(50L, 0L, 0L, 50L, 75L, 100L, 50L, 0L, 50L, 0L,
25L, 50L, 50L, 75L, 75L, 75L, 0L, 75L, 75L, 75L, 0L, 25L, 75L,
75L, 0L, 75L, 100L, 0L, 25L, 100L), c(75L, 0L, 0L, 50L, 100L,
50L, 75L, 75L
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