The relationship between the conditional sum of squares and the exact likelihood for autoregressive moving average models
نویسنده
چکیده
In this note I will study the relationship between the conditional sum of squares (CSS) estimator of moving averages and the maximum likelihood (ML) estimator. I will show that the CSS estimator can be converted into the ML estimator via the use of the EM algorithm. A by-product of the EM algorithm is an expression for the likelihood function and the score. This argument generalizes to autoregressive moving average (ARMA) models.
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