论文标题
来自Lévy驱动的存储系统中离散工作负载观察的输入估计
Input estimation from discrete workload observations in a Lévy-driven storage system
论文作者
论文摘要
我们的目标是估算从eqpaced工作负载观测值样本中估算出莱维驱动的存储系统的特征指数。估计器依赖于与在指数分布的采样时间下工作负载的拉普拉斯 - 斯泰尔特式转换相关的大概矩方程。对于任何观察网格，估计器均保持一致。此外，高频采样方案为一类输入过程产生渐近正常的估计误差。通过模拟实验建议并评估一种以更有效的方式使用可用信息的重采样方案。
Our goal is to estimate the characteristic exponent of the input to a Lévy-driven storage system from a sample of equispaced workload observations. The estimator relies on an approximate moment equation associated with the Laplace-Stieltjes transform of the workload at exponentially distributed sampling times. The estimator is pointwise consistent for any observation grid. Moreover, a high frequency sampling scheme yields asymptotically normal estimation errors for a class of input processes. A resampling scheme that uses the available information in a more efficient manner is suggested and assessed via simulation experiments.
