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On weighted Poisson distributions and processes, with associated inference and applications

Thesis (PhD (Mathematical Statistics))--University of Pretoria, 2020.

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Other Authors: Visagie, Jaco
Format: Thesis
Language:English
Published: University of Pretoria 2020
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access_status_str Open Access
author2 Visagie, Jaco
author_browse Visagie, Jaco
author_facet Visagie, Jaco
collection Thesis
dc_rights_str_mv © 2019 University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria.
description Thesis (PhD (Mathematical Statistics))--University of Pretoria, 2020.
format Thesis
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institution University of Pretoria (South Africa)
language English
last_indexed 2026-06-10T12:40:26.265Z
license_str Other — see source repository
provenance_str_mv Harvested via OAI-PMH from UPSpace — University of Pretoria Institutional Repository
publishDate 2020
publishDateRange 2020
publishDateSort 2020
publisher University of Pretoria
publisherStr University of Pretoria
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source_str UPSpace — University of Pretoria Institutional Repository
spelling oai:repository.up.ac.za:2263/77387 On weighted Poisson distributions and processes, with associated inference and applications Visagie, Jaco albert@mijburgh.co.za Balakrishnan, Narayanaswamy Mijburgh, Philip Albert UCTD Mathematical Statistics Thesis (PhD (Mathematical Statistics))--University of Pretoria, 2020. In this thesis, weighted Poisson distributions and processes are investigated, as alternatives to Poisson distributions and processes, for the modelling of discrete data. In order to determine whether the use of a weighted Poisson distribution can be theoretically justified over the Poisson, goodness-of-fit tests for Poissonity are examined. In addition to this research providing an overarching review of the current Poisson goodness-of-fit tests, it is also examined how these tests perform when the alternative distribution is indeed realised from a weighted Poisson distribution. Similarly, a series of tests are discussed which can be used to determine whether a sample path is realised from a homogeneous Poisson process. While weighted Poisson distributions and processes have received some attention in the literature, the list of potential weight functions with which they can be augmented is limited. In this thesis 26 new weight functions are presented and their statistical properties are derived in closed-form, both in terms of distributions and processes. These new weights allow, what were already very flexible models, to be applied to a range of new practical situations. In the application sections of the thesis, the new weighted Poisson models are applied to many different discrete datasets. The datasets originate from a wide range of industries and situations. It is shown that the new weight functions lead to weighted Poisson distributions and processes that perform favourably in comparison to the majority of current modelling methodologies. It is demonstrated that the weighted Poisson distribution can not only model data from Poisson, binomial and negative binomial distributions, but also some more complex distributions like the generalised Poisson and COM-Poisson. UP Postgraduate Research Support Bursary UP Postgraduate Study Abroad Bursary STATOMET Bursary. SASA/NRF Academic Statistics Bursary Statistics PhD (Mathematical Statistics) Unrestricted 2020-12-17T11:49:54Z 2020-12-17T11:49:54Z 2021 2020 Thesis * http://hdl.handle.net/2263/77387 en © 2019 University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria. application/pdf University of Pretoria
spellingShingle UCTD
Mathematical Statistics
On weighted Poisson distributions and processes, with associated inference and applications
title On weighted Poisson distributions and processes, with associated inference and applications
title_full On weighted Poisson distributions and processes, with associated inference and applications
title_fullStr On weighted Poisson distributions and processes, with associated inference and applications
title_full_unstemmed On weighted Poisson distributions and processes, with associated inference and applications
title_short On weighted Poisson distributions and processes, with associated inference and applications
title_sort on weighted poisson distributions and processes with associated inference and applications
topic UCTD
Mathematical Statistics
url http://hdl.handle.net/2263/77387