From: A generalization to the log-inverse Weibull distribution and its applications in cancer research
Model | Estimates | Log- Likelihood | AIC | BIC | AICc | CAIC |
---|---|---|---|---|---|---|
ExLIWD | a = − 243.995 | −181.9026 | 371.805 | 379.610 | 372.656 | 383.610 |
b = 256.509 | ||||||
c = 46.217 | ||||||
δ = 44.601 | ||||||
GIGWD | α = 86.370 | − 182.2115 | 372.423 | 380.227 | 373.274 | 384.227 |
β = 0.1510 | ||||||
λ = 5.88 0 | ||||||
γ = 7.270 | ||||||
KMIWD | a = 130.900 | − 184.5836 | 379.1672 | 389.382 | 380.343 | 394.382 |
δ = 0.2960 | ||||||
ρ = 0.0550 | ||||||
σ = 0.0075 | ||||||
β = 229.80 | ||||||
GIWD | σ = 5.0810 | −184.641 | 375.281 | 381.134 | 375.7811 | 384.134 |
β = 004890 | ||||||
ϑ = 1.5890 | ||||||
EPLD | α = 1.7626 | − 187.5605 | 381.121 | 386.974 | 381.621 | 389.974 |
β = 0.4448 | ||||||
θ = 0.2598 | ||||||
ELIWD | a = −53.5756 | − 190.822 | 389.644 | 397.448 | 390.495 | 401.448 |
b = 57.6963 | ||||||
c = 25.3954 | ||||||
IGWD | λ = 13.6790 | −195.024 | 396.048 | 401.901 | 396.548 | 404.901 |
β = 0.4216 | ||||||
α = 1.1830 | ||||||
LGIWD | μ = −1.4166 | −198.266 | 402.532 | 408.385 | 403.032 | 411.385 |
σ = 76.5670 | ||||||
γ = 2.8988 | ||||||
LD | α = 10.01 | − 202.0545 | 410.109 | 415.962 | 410.609 | 418.962 |
β = 1000 | ||||||
θ = 0.0148 | ||||||
GLD | α = 0.02035 | − 3019.677 | 6045.354 | 6051.207 | 6045.854 | 6054.207 |
β = 0.0028 | ||||||
θ = 0.8194 |