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Nonparametric estimation of the spectral density of amplitude-modulated time series with missing observations

机译:缺少观测值的调幅时间序列频谱密度的非参数估计

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摘要

Consider a real-valued and second-order stationary time series with mean zero. The aim is to estimate its spectral density. A minimax solution of this problem is known when either the time series is observed directly, or some observations are missed according to an independent Bernoulli process, or for some special cases when the time series is multiplied by an amplitude-modulating time series with known distribution. It is shown that if a time series of interest, a Bernoulli time series defining missing mechanism, and an amplitude-modulating time series are mutually independent, then the shape of spectral density of an underlying time series of interest can be estimated with the minimax rate known for the case of direct observations. Furthermore, in some special cases the spectral density can be estimated with the minimax rate known for directly observed time series of interest.
机译:考虑均值为零的实值和二阶平稳时间序列。目的是估计其光谱密度。当直接观察时间序列,或根据独立的伯努利过程错过了一些观察值时,或者对于某些特殊情况,当时间序列乘以具有已知分布的调幅时间序列时,已知此问题的极小极大解。结果表明,如果感兴趣的时间序列,定义丢失机制的伯努利时间序列和调幅时间序列相互独立,则可以用最小最大速率估算感兴趣的基础时间序列的频谱密度形状。因直接观察而著称。此外,在某些特殊情况下,可以使用直接观察到的感兴趣时间序列已知的最小最大速率来估计光谱密度。

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