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Maximum quasi‐likelihood estimation for the near(2) model

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  • S. Perera

Abstract

. Maximum quasi‐likelihood estimation is investigated for the NEAR(2) model, an autoregressive time series model with marginal exponential distributions. In certain regions of the parameter space, simulations indicate that maximum quasi‐likelihood estimators perform better than two‐stage conditional least squares estimators in terms of the per cent of estimates falling in the parameter space. The problem of out‐of‐range estimates is shown to be caused by the lack of information in the data rather than the characteristics of the method of estimation.

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  • S. Perera, 2004. "Maximum quasi‐likelihood estimation for the near(2) model," Journal of Time Series Analysis, Wiley Blackwell, vol. 25(5), pages 723-732, September.
    • Handle: RePEc:bla:jtsera:v:25:y:2004:i:5:p:723-732
    DOI: 10.1111/j.1467-9892.2004.01886.x
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    References listed on IDEAS

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    1. L. Billard & Fouad Y. Mohamed, 1991. "ESTIMATION OF THE PARAMETERS OF AN EAR(p) PROCESS," Journal of Time Series Analysis, Wiley Blackwell, vol. 12(3), pages 179-192, May.
    2. Kung‐sik Chan, 1988. "ON THE EXISTENCE OF THE STATIONARY AND ERGODIC NEAR(p) MODEL," Journal of Time Series Analysis, Wiley Blackwell, vol. 9(4), pages 319-328, July.
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