Construction of prior probability distribution using a mollified functional

توێژەران

  • S.J. Yaga*† * Department of Mathematical Sciences, University of Maiduguri, Maiduguri, Nigeria
  • N.P. Dibal* Department of Statistics, University of Agriculture, Makurdi, Nigeria
  • I.E. Gongsin* College of Medical Sciences, Department of Community Medicine, University of Maiduguri, Maiduguri, Nigeria
  • H.R. Bakari*
  • S.C. Nwaosu‡
  • Zara Wudiri§

##semicolon##

mollifier##common.commaListSeparator## mfdip##common.commaListSeparator## invariance property##common.commaListSeparator## prior probability distribution##common.commaListSeparator## parametric functions

پوختە

In this paper, we proposed a new class of prior distribution, the Mollified Functional Data Informative Prior using the convolution of standard scaled mollified functional and sampling distribution of the data. We also show that the MFDIP possesses the invariance property to reparameterization and apply the MFDIP to derive the prior for exponential probability distribution.

##submission.downloads##

بڵاو کرایەوە

2023-09-30

چۆنییەتی بەکارهێنانی سەرچاوە

Yaga*†, S. ., Dibal*, N. ., Gongsin*, I. ., Bakari*, H. ., Nwaosu‡, S. ., & Wudiri§, Z. . (2023). Construction of prior probability distribution using a mollified functional . International Journal of Mathematical Analysis and Modelling, 5(4). Retrieved from https://tnsmb.org/journal/index.php/ijmam/article/view/70

ژمارە

بەرگ 5 ژمارە 4 (2022): Volume 5, Issue 4 (Nov.) 2022

بەش

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