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回归误设时GLS在RegARIMA及相关模型一步预测中的最优性AI 解读

We consider the modeling of a time series described by a linear regression component whose regressor sequence satisfies the generalized asymptotic sample second moment stationarity conditions of Grenander (1954, Annals of Mathematical Statistics 25, 252–272). The associated disturbance process is only assumed to have sample second moments that converge with increasing series length, perhaps after a differencing operation. The model's regression component, which can be…

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时间序列数组族样本二阶矩的一致收敛AI 解读

We consider abstractly defined time series arrays y t(T), 1 \le t\le T, requiring only that their sample lagged second moments converge and that their end values y1+j(T) and yT-j(T) be of order less than T½ for each j \ge 0. We show that,under quite general assumptions, various types of arrays that arise naturally in time series analysis have these properties,including regression residuals from a time series regression, seasonal adjustments and infinite variance processes…

X-12-ARIMA 季节调整程序的新功能与方法——回复AI 解读

David F. Findley, Brian C. Monsell, William R. Bell, Mark C. Otto, Bor-Chung Chen, [New Capabilities and Methods of the X-12-ARIMA Seasonal-Adjustment Program]: Reply, Journal of Business & Economic Statistics, Vol. 16, No. 2 (Apr., 1998), pp. 169-177

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X-12-ARIMA 季节调整程序的新功能与方法AI 解读

X-12-ARIMA is the Census Bureau's new seasonal-adjustment program. It provides four types of enhancements to X-ll-ARIMA—(1) alternative seasonal, trading-day, and holiday effect adjustment capabilities that include adjustments for effects estimated with user-defined regressors; additional seasonal and trend filter options; and an alternative seasonal-trend-irregular decomposition; (2) new diagnostics of the quality and stability of the adjustments achieved under the options…

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非高斯平稳时间序列的独立同分布创新移动平均表示唯一性AI 解读

Full-spectrum, non-Gaussian stationary series can have at most one representation as a moving average of independent and identically distributed random variables having finite moments of all orders.

非高斯平稳时间序列的独立同分布创新移动平均表示的唯一性AI 解读

Full-spectrum, non-Gaussian stationary series can have at most one representation as a moving average of independent and identically distributed random variables having finite moments of all orders.

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