Show simple item record

dc.contributor.authorGuerrero, Matheus B.
dc.contributor.authorBarreto-Souza, Wagner
dc.contributor.authorOmbao, Hernando
dc.date.accessioned2020-12-01T10:52:22Z
dc.date.available2020-12-01T10:52:22Z
dc.date.issued2020-04-18
dc.identifier.urihttp://hdl.handle.net/10754/666185
dc.description.abstractINteger Auto-Regressive (INAR) processes are usually defined by specifying the innovations and the operator, which often leads to difficulties in deriving marginal properties of the process. In many practical situations, a major modeling limitation is that it is difficult to justify the choice of the operator. To overcome these drawbacks, we propose a new flexible approach to build an INAR model: we pre-specify the marginal and innovation distributions. Hence, the operator is a consequence of specifying the desired marginal and innovation distributions. Our new INAR model has both marginal and innovations geometric distributed, being a direct alternative to the classical Poisson INAR model. Our proposed process has interesting stochastic properties such as an MA($\infty$) representation, time-reversibility, and closed-forms for the transition probabilities $h$-steps ahead, allowing for coherent forecasting. We analyze time-series counts of skin lesions using our proposed approach, comparing it with existing INAR and INGARCH models. Our model gives more adherence to the data and better forecasting performance.
dc.publisherarXiv
dc.relation.urlhttps://arxiv.org/pdf/2004.08667
dc.rightsArchived with thanks to arXiv
dc.titleInteger-valued autoregressive process with flexible marginal and innovation distributions
dc.typePreprint
dc.contributor.departmentKing Abdullah University of Science and Technology, Thuwal, Saudi Arabia.
dc.contributor.departmentStatistics Program
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.eprint.versionPre-print
dc.contributor.institutionUniversidade Federal de Minas Gerais, Belo Horizonte, Brazil.
dc.identifier.arxivid2004.08667
kaust.personGuerrero, Matheus B.
kaust.personBarreto-Souza, Wagner
kaust.personOmbao, Hernando
refterms.dateFOA2020-12-01T10:52:54Z


Files in this item

Thumbnail
Name:
Preprintfile1.pdf
Size:
759.8Kb
Format:
PDF
Description:
Pre-print

This item appears in the following Collection(s)

Show simple item record