<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE ArticleSet PUBLIC "-//NLM//DTD PubMed 2.7//EN" "https://dtd.nlm.nih.gov/ncbi/pubmed/in/PubMed.dtd">
<ArticleSet>
<Article>
<Journal>
				<PublisherName>Iranian Statistical Society</PublisherName>
				<JournalTitle>Journal of the Iranian Statistical Society</JournalTitle>
				<Issn>1726-4057</Issn>
				<Volume>11</Volume>
				<Issue>2</Issue>
				<PubDate PubStatus="epublish">
					<Year>2022</Year>
					<Month>07</Month>
					<Day>23</Day>
				</PubDate>
			</Journal>
<ArticleTitle>Integer Valued AR(1) with Geometric Innovations</ArticleTitle>
<VernacularTitle>مدل AR صحیح مقدار با تغییرات هندسی</VernacularTitle>
			<FirstPage>173</FirstPage>
			<LastPage>190</LastPage>
			<ELocationID EIdType="pii">253688</ELocationID>
			
			
			<Language>EN</Language>
<AuthorList>
<Author>
					<FirstName>Mansour</FirstName>
					<LastName>Aghababaei Jazi</LastName>
<Affiliation></Affiliation>

</Author>
<Author>
					<FirstName>Geoff</FirstName>
					<LastName>Jones</LastName>
<Affiliation></Affiliation>

</Author>
<Author>
					<FirstName>Chin-Diew</FirstName>
					<LastName>Lai</LastName>
<Affiliation></Affiliation>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2022</Year>
					<Month>07</Month>
					<Day>23</Day>
				</PubDate>
			</History>
		<Abstract>The classical integer valued first-order autoregressive (INA- R(1)) model has been defined on the basis of Poisson innovations. This model has Poisson marginal distribution and is suitable for modeling equidispersed count data. In this paper, we introduce an modification of the INAR(1) model with geometric innovations (INARG(1)) for model- ing overdispersed count data. We discuss some structural mathematical properties of the process comparing with classical INAR(1). Also, the superiority of the model in contrast with the INAR(1) is shown by some real time series.</Abstract>
		<ObjectList>
			<Object Type="keyword">
			<Param Name="value">Binomial thinning operator</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">conditional maximum likeli- hood estimation</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">infinitely divisible distributions</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">mixture distributions</Param>
			</Object>
		</ObjectList>
<ArchiveCopySource DocType="pdf">https://jirss.irstat.ir/article_253688_fe142115b95dbd049f5075ccd24ce1ad.pdf</ArchiveCopySource>
</Article>
</ArticleSet>
