Exponential distribution {shannon} | R Documentation |
Compute the Shannon, Rényi, Havrda and Charvat, and Arimoto entropies of the exponential distribution
Description
Compute the Shannon, Rényi, Havrda and Charvat, and Arimoto entropies of the exponential distribution.
Usage
Se_exp(alpha)
re_exp(alpha, delta)
hce_exp(alpha, delta)
ae_exp(alpha, delta)
Arguments
alpha |
The strictly positive scale parameter of the exponential distribution ( |
delta |
The strictly positive parameter ( |
Details
The following is the probability density function of the exponential distribution:
f(x)=\alpha e^{-\alpha x},
where x > 0
and \alpha > 0
.
Value
The functions Se_exp, re_exp, hce_exp, and ae_exp provide the Shannon entropy, Rényi entropy, Havrda and Charvat entropy, and Arimoto entropy, respectively, depending on the selected parametric values of the exponential distribution and \delta
.
Author(s)
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.
References
Balakrishnan, K. (2019). Exponential distribution: theory, methods and applications. Routledge.
Singh, A. K. (1997). The exponential distribution-theory, methods and applications, Technometrics, 39(3), 341-341.
Arimoto, S. (1971). Information-theoretical considerations on estimation problems. Inf. Control, 19, 181–194.
See Also
Examples
Se_exp(0.2)
delta <- c(1.5, 2, 3)
re_exp(0.2, delta)
hce_exp(0.2, delta)
ae_exp(0.2, delta)