Penalised maximum likelihood estimation for fractional Gaussian processes
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We apply and extend Firth's (1993) modified score estimator to deal with a class of stationary Gaussian long-memory processes. Our estimator removes the first order bias of the maximum likelihood estimator. A small simulation study reveals the reduction in the bias is considerable, while it does not inflate the corresponding mean squared error.
[1] Marius Ooms,et al. Computational aspects of maximum likelihood estimation of autoregressive fractionally integrated moving average models , 2003, Comput. Stat. Data Anal..