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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

\(\left[ 3.42021025 ; 3.46662952\right]\)