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shannon (version 0.2.0)

Exponentiated Weibull distribution: Compute the Shannon, Rényi, Havrda and Charvat, and Arimoto entropies of the exponentiated Weibull distribution

Description

Compute the Shannon, Rényi, Havrda and Charvat, and Arimoto entropies of the exponentiated Weibull distribution.

Usage

se_ew(a, beta, zeta)
re_ew(a, beta, zeta, delta)
hce_ew(a, beta, zeta, delta)
ae_ew(a, beta, zeta, delta)

Value

The functions se_ew, re_ew, hce_ew, and ae_ew provide the Shannon entropy, Rényi entropy, Havrda and Charvat entropy, and Arimoto entropy, respectively, depending on the selected parametric values of the exponentiated Weibull distribution and δ.

Arguments

a

The strictly positive shape parameter of the exponentiated Weibull distribution (a>0).

beta

The strictly positive scale parameter of the baseline Weibull distribution (β>0).

zeta

The strictly positive shape parameter of the baseline Weibull distribution (ζ>0).

delta

The strictly positive parameter (δ>0) and (δ1).

Author

Muhammad Imran, Christophe Chesneau and Farrukh Jamal

R implementation and documentation: Muhammad Imran <imranshakoor84@yahoo.com>, Christophe Chesneau <christophe.chesneau@unicaen.fr> and Farrukh Jamal farrukh.jamal@iub.edu.pk.

Details

The following is the probability density function of the exponentiated Weibull distribution: f(x)=aζβζxζ1e(xβ)ζ[1e(xβ)ζ]a1, where x>0, a>0, β>0 and ζ>0.

References

Nadarajah, S., Cordeiro, G. M., & Ortega, E. M. (2013). The exponentiated Weibull distribution: a survey. Statistical Papers, 54, 839-877.

See Also

re_exp, re_wei, re_ew

Examples

Run this code
se_ew(0.8, 0.2, 0.8)
delta <- c(1.5, 2, 3)
re_ew(1.2, 1.2, 1.4, delta)
hce_ew(1.2, 1.2, 1.4, delta)
ae_ew(1.2, 1.2, 1.4, delta)

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