Fixed Size Confidence Regions for Parameters of Stationary Processes Based on a Minimum Contrast Estimator
Fixed Size Confidence Regions for Parameters of Stationary Processes Based on a Minimum Contrast Estimator
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发表时间：
2005
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通讯作者：
Takayuki Shiohama
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作者：
Takayuki Shiohama
对于具有零均值和谱密度的平稳过程参数，提出了一种利用最小对比度估计器构造未知参数的固定大小置信椭球区域的序贯方法.置信椭圆是渐近一致的，相关的停止规则是渐近有效的，因为当假设的参数模型是正确的时，区域的大小变得很小。蒙特卡洛模拟研究我们提出的顺序程序的性能。
For parameters of stationary processes with zero mean and spectral density, sequential procedures are proposed for constructing fixed size confidence ellipsoidal regions for unknown parameters using a minimum contrast estimator. The confidence ellipsoids are shown to be asymptotically consistent and the associated stopping rules are shown to be asymptotically efficient as the size of the region becomes small when the assumed parametric model is correct. Monte Carlo simulations are given to investigate the performance of our proposed sequential procedures.