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Change monitoring of distribution in time series models is an important issue.This paper proposes a procedure for monitoring changes in the error distribution of autoregressive time series,which is based on a weighed empirical process of residuals with weights equal to the regressors.The asymptotic properties of our monitoring statistic are derived under the null hypothesis of no change in distribution.The finite sample properties are investigated by a simulation.As it turns out,the procedure is not only able to detect distributional changes but also changes in the regression coefficient and mean.Finally,we apply the statistic to a groups of financial data. 相似文献
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A multiscale information measure (MIM), calculable from per-pixel wavelet coefficients, but relying on global statistics of synthetic aperture radar (SAR) image, is proposed. It fully exploits the variations in speckle pattern when the image resolution varies from course to fine, thus it can capture the intrinsic texture of the scene backscatter and the texture due to speckle simultaneously. Graph spectral segmen- tation methods based on MIM and the usual similarity measure are carried out on two real SAR images. Experimental results show that MIM can characterize texture information of SAR image more effectively than the commonly used similarity measure. 相似文献
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研究随机设计下噪声为厚尾随机变量时非参数函数中的变点估计问题.首先,通过设计变换将随机设计转化为等间距固定设计,进而利用小波方法估计变换后的变点的位置,再利用逆设计变换求得随机设计下变点位置的估计,并给出估计的收敛速度.模拟研究结果说明对于无穷方差厚尾过程中的变点估计问题小波方法是有效的. 相似文献
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考虑响应变量带有一般测量误差的非线性半参数模型.在核实数据的帮助下,利用半参数降维技术构造未知参数和非参数函数的估计.在一定条件下证明未知参数估计的渐近正态性和非参数函数估计的最优收敛速度.通过数值模拟说明所提估计方法在有限样本下的有效性. 相似文献
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研究一类新的非参数回归模型回归函数的核估计问题,其中误差项为一阶非参数自回归方程.通过重复利用Watson-Nadaraya核估计方法,构造了回归函数及误差回归函数的估计量分别为m(.)和ρ(.),在适当的条件下,证明了估计量m(.)和ρ(.)的渐近正态性. 相似文献
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研究自回归条件异方差(ARCH)模型的多变点检验问题.提出一种拟似然比检验统计量,并在原假设下给出统计量的极限分布.在假设检验过程中得到变点个数的一致估计.数值模拟与实例分析说明了方法的合理性. 相似文献
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考虑固定设计下具有一阶非参数自回归误差的线性模型,构造了参数和非参数函数的N-W核估计,在适当的条件下,证明了参数估计的强相合性,同时给出了非参数函数估计的渐近正态性. 相似文献
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非线性模型滞后相依的广义互信息检验 总被引:1,自引:0,他引:1
The general mutual information (GMI) and general conditional mutual information (GCMI) are considered to measure lag dependences in nonlinear time series. Both of the measures have the property of invariance with transform. The statistics based on GMI and GCMI are estimated using the correlation integral. Under the hypothesis of independent series, the estimators have Gaussian asymptotic distributions. Simulations applied to generated nonlinear series demonstrate that the methods appear to find frequently the correct lags. 相似文献