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ESTIMATION OF A REGRESSION WITH THE PULSE TYPE NOISE FROM DISCRETE DATA

机译:从离散数据估计具有脉冲型噪声的回归

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This paper considers the problem of estimating parameters in a periodic regression in continuous time with a semimartingale noise by discrete time observations. Improved estimates for the regression parameters are proposed. It is established that under some general conditions these estimates have an advantage in the mean square accuracy over the least squares estimates. The asymptotic minimaxity of the improved estimates has been proved in the robust risk sense. 'The properties of the proposed procedure for the models with non-Gaussian noises of pulse type have been studied. The pulse disturbances have random intensity and occur at random times which form a Poisson process.
机译:本文考虑了通过离散时间观测来估计具有半mart噪声的连续时间的周期性回归中的参数估计问题。提出了改进的回归参数估计。可以确定的是,在某些一般条件下,这些估计在均方根精度方面优于最小二乘方估计。在稳健的风险意义上证明了改进估计的渐近最小极大。 '已经研究了针对具有脉冲类型的非高斯噪声的模型的拟议程序的性质。脉冲扰动具有随机强度,并在随机时间发生,这形成了泊松过程。

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