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A Study for Missing Values in PINAR(1)T Processes

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  • Boting Jia
  • Dehui Wang
  • Haixiang Zhang

Abstract

In this paper, we propose several approaches to estimate the parameters of the periodic first-order integer-valued autoregressive process with period T (PINAR(1)T) in the presence of missing data. By using incomplete data, we propose two approaches that are based on the conditional expectation and conditional likelihood to estimate the parameters of interest. Then we study three kinds of imputation methods for the missing data. The performances of these approaches are compared via simulations.

Suggested Citation

  • Boting Jia & Dehui Wang & Haixiang Zhang, 2014. "A Study for Missing Values in PINAR(1)T Processes," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 43(22), pages 4780-4789, November.
    • Handle: RePEc:taf:lstaxx:v:43:y:2014:i:22:p:4780-4789
    DOI: 10.1080/03610926.2012.717664
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