Hi rooters,
I am currently performing an unbinned maximum likelihood fit to extract two parameters (a1, a2) from N events. The likelihood function is constructed as:
-lnL=Sum_{i=0}^{N} ln W(\xi_i; a1,a2)
I then attempted to incorporate a constraint between a1 and a2 using the Lagrange multiplier method, modifying the likelihood function to:
-lnL=Sum_{i=0}^{N} ln W(\xi_i; a1,a2) + lambda Func(a1, a2)
However, when minimizing -lnL using TMinuit, the fit consistently hits the boundary regardless of how I adjust the range of lambda, resulting in failed convergence. I would like to ask:
- Whether my construction of the likelihood function using the Lagrange multiplier method is correct
- Whether TMinuit is an appropriate tool for this constrained minimization approach
thanks for your attention,
Yupeng