Some Results on the Non-Homogeneous Hofmann Process

Jose Alfredo Jimenez Moscoso and Gerson Yahir Palomino Velandia

A chapter in Applied Probability Theory - New Perspectives, Recent Advances and Trends from IntechOpen

Abstract: The classical counting processes (Poisson and negative binomial) are the most traditional discrete counting processes (DCPs); however, these are based on a set of rigid assumptions. We consider a non-homogeneous counting process (which we name non-homogeneous Hofmann process - NHP) that can generate the classical counting processes (CCPs) as special cases, and also allows modeling counting processes for event history data, which usually exhibit under- or over-dispersion. We present some results of this process that will allow us to use it in other areas and establish both the probability mass function (pmf) and the cumulative distribution function (cdf) using transition intensities. This counting process (CP) will allow other researchers to work on modelling the CP, where data dispersion exists in an efficient and more flexible way.

Keywords: mixed Poisson Process; Hofmann process; variance-to-mean ratio; transition intensity (search for similar items in EconPapers)
JEL-codes: C25 C83 (search for similar items in EconPapers)
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.intechopen.com/chapters/83171 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ito:pchaps:287361

DOI: 10.5772/intechopen.106422

Access Statistics for this chapter

More chapters in Chapters from IntechOpen
Bibliographic data for series maintained by Slobodan Momcilovic ().