The Inverse Kullback–Leibler Method for Fitting Vector Moving Averages
提出一种用逆谱的Kullback-Leibler差异估计向量移动平均过程的新方法，得到系数直接公式并保证稳定，给出渐近结果和性能分析，在零售数据上展示应用。
A new method for the estimation of a vector moving average (VMA) process is presented. The technique uses Kullback–Leibler discrepancy with inverse spectra, and yields a Yule–Walker system of equations in inverse autocovariances for the VMA coefficients. This provides a direct formula for the coefficients, which always results in a stable matrix polynomial. The paper provides asymptotic results, as well as an analysis of the method's performance, in terms of speed, bias, and precision. Applications to preliminary estimation of VMA models are discussed, and the method is illustrated on retail data.