A Study for Missing Values in PINAR(1)TProcesses

Autor:	Haixiang Zhang, Boting Jia, Dehui Wang
Rok vydání:	2014
Předmět:	Statistics and Probability Conditional likelihood Autoregressive model Statistics Imputation (statistics) Missing data Conditional expectation Mathematics
Zdroj:	Communications in Statistics - Theory and Methods. 43:4780-4789
ISSN:	1532-415X 0361-0926
DOI:	10.1080/03610926.2012.717664
Popis:	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.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::1a5d4247b7d4aa37a240b8acf2f212f7 https://doi.org/10.1080/03610926.2012.717664 Zobrazit plný text záznamu