Symmetric Regression Model for Temporal Data

Francisco JA Cysneiros
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Francisco JA Cysneiros: Departamento de Estatística, CCEN-UFPE - Cidade Universitária, Brazil

Biostatistics and Biometrics Open Access Journal, 2018, vol. 5, issue 2, 44-45

Abstract: The pioneering work for non-Gaussian time series developed by Heyde & Feigin [1] who developed Poisson conditional autoregressive range. Cox [2] studied the autocorrelation of data, featuring two classes of time-dependent models: models conditioned on past observations and based on latent processes. In addition, Zeger [3] including the past and present of covariates in this model. Zeger & Qaqish [4] developed Markov chain for time series. Li [5] included moving averages models component in this model.

Keywords: Biometrics Open Access Journal; Biostatistics and Biometrics; Biostatistics and Biometrics Open Access Journal; Open Access Journals; biometrics journal; biometrics articles; biometrics journal reference; biometrics journal impact factor; biometrics and biostatistics journal impact factor; journal of biometrics; open access juniper publishers; juniper publishers reivew (search for similar items in EconPapers)
Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:adp:jbboaj:v:5:y:2018:i:2:p:44-45

DOI: 10.19080/BBOAJ.2018.05.555657

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