论文检索

无限方差分数 ARIMA 模型的参数估计AI 解读

Consider the fractional ARIMA time series with innovations that have infinite variance. This is a finite parameter model which exhibits both long-range dependence (long memory) and high variability. We prove the consistency of an estimator of the unknown parameters which is based on the periodogram and derive its asymptotic distribution. This shows that the results of Mikosch, Gadrich, Klüppelberg and Adler for ARMA time series remain valid for fractional ARIMA with…

具有长记忆的无限方差稳定移动平均过程AI 解读

We investigate the notion of long memory for infinite variance moving averages with stable non-Gaussian innovations and regularly varying coefficients. Regularly varying coefficients decay to zero like jPL(j) as j → ∞, where L is a slowly varying function. We study the asymptotic behavior of two measures of dependence, the codifference and the covariation, which are extensions of the covariance.