The Asymmetrical n-k Distribution
AbstractThis paper specializes and parameterizes the general result presented elsewhere in the literature in order to propose, fully characterize, and investigate the Asymmetrical − Distribution. It yields estimators for the involved parameters and uses field measurements to validate the distribution. The Asymmetrical − Distribution includes, as special cases, important distributions such as Rayleigh, Rice, Hoyt, Nakagami-q, and One-Sided Gaussian. The fact that the Asymmetrical − Distribution has one more parameter than the well-known distributions renders it more flexible. Of course, in situations in which those distributions included in it give good results a better fit is given by the Asymmetrical − Distribution. In addition, in many other situations in which these distributions give poor results a good fit may be found through the Asymmetrical − Distribution. More specifically, its non-monomodal feature finds applications in several circumstances, examples of which are given in this paper.
How to Cite
Daoud Yacoub, M., Fraidenraich, G., B. Tercius, H., & C. Martins, F. (2015). The Asymmetrical n-k Distribution. Journal of Communication and Information Systems, 20(3). https://doi.org/10.14209/jcis.2005.25
Copyright (c) 2015 Michel Daoud Yacoub, Gustavo Fraidenraich, Hermano B. Tercius, Fábio C. Martins
Authors who publish in this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
- Authors can enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) before and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).