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Table 5 MLE estimates for the parameters of \(\mathcal {EW}\) distribution with Nelore data via BFGS, SANN, and Nelder–Mead algorithms

From: Analyzing and solving the identifiability problem in the exponentiated generalized Weibull distribution

Methods Parameters Estimates SE Confidence Interval (0.95)
BFGS b 40.34715566 1.479593e+01 \(\left[ 40.13701054; 40.55730079\right]\)
c 0.01018772 5.397052e−04 \(\left[ 0.01018006; 0.01019539\right]\)
\(\beta\) 2.85355684 1.892528e−01 \(\left[ 2.85086890; 2.85624478\right]\)
SANN b 4.109734969 0.8629722253 \(\left[ 4.097478262 ; 4.121991676\right]\)
c 0.007648857 0.0003420323 \(\left[ 0.007643999 ; 0.007653715\right]\)
\(\beta\) 2.942210704 0.2948368954 \(\left[ 2.938023166 ; 2.946398243\right]\)
Nelder–Mead b 58.782451666 67.03485145 \(\left[ 56.87827328 ; 60.68663006\right]\)
c 0.009599516 0.00169215 \(\left[ 0.00955145 ; 0.00964758\right]\)
\(\beta\) 3.443419884 0.81707386 \(\left[ 3.42021025 ; 3.46662952\right]\)