
<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/">
  <dc:date>2020</dc:date>
  <dc:contributor>Nastić, Aleksandar 1978-</dc:contributor>
  <dc:contributor>Đorđević, Miodrag</dc:contributor>
  <dc:contributor>Ristić, Miroslav</dc:contributor>
  <dc:contributor>Popović, Predrag</dc:contributor>
  <dc:format>[8], 115 str.</dc:format>
  <dc:format>2548869 bytes</dc:format>
  <dc:title xml:lang="srp">Nenegativni celobrojni autoregresivni procesi u slučajnoj sredini generisani geometrijskim brojačkim nizovima</dc:title>
  <dc:language>srp</dc:language>
  <dc:creator>Laketa, Petra N. 1991-</dc:creator>
  <dc:identifier>https://phaidrani.ni.ac.rs/o:1687</dc:identifier>
  <dc:identifier>cobiss:28177929</dc:identifier>
  <dc:identifier>thesis:7995</dc:identifier>
  <dc:rights>http://creativecommons.org/licenses/by-nc-nd/2.0/at/legalcode</dc:rights>
  <dc:description xml:lang="eng">Here are analyzed integer autoregressive (INAR) processes in the random environment generated by geometric counting series. Firstly, the first order random environment INAR model is introduced. Later, random environment INAR models of higher order, as well as their general form, are defined. Finally, the bivariate model based on the bivariate random process is defined. The properties of all introduced models are analyzed. Estimation of unknown parameters is given and validate on the simulated data. Model quality is confirmed by application on the real-life data, comparing results with the competitive models.</dc:description>
  <dc:description xml:lang="srp">Biobibliografija: str. 113-115;Bibliografija: str. 109-112.  Datum odbrane: 17.10.2020. Mathematical statistics, statistics of random processes</dc:description>
  <dc:type>info:eu-repo/semantics/bachelorThesis</dc:type>
</oai_dc:dc>
