Variable Window Scan Statistics for Normal Data
Variable Window Scan Statistics for Normal Data
复制标题
正常数据的可变窗口扫描统计
DOI：
10.1080/03610926.2013.782201
复制
发表时间：
2014
期刊：
影响因子：
--
通讯作者：
J. Glaz
中科院分区：
文献类型：
--
作者：
Xiao Wang;J. Glaz
本文对连续分布的独立同分布观测值，导出了二维扫描统计量分布的近似和不等式。这些近似和不等式的准确性进行了调查正常的模型。讨论了均值和方差已知和未知的情况。在一维和二维固定窗口扫描统计量分布近似的基础上，引入了可变窗口扫描统计量。我们调查的性能，这些变量窗口扫描统计量作为测试统计量检测的本地变化的平均值的正态分布。通过利用R算法的多元正态分布和由Genz和Bretz（2009）建立的分布，数值结果来评估实施可变窗口扫描统计的效率，并通过功效计算比较它们的性能，与固定窗口扫描统计。从数值结果可以明显看出，如果发生变化的窗口的尺寸未知，则可变窗口扫描统计优于固定窗口扫描统计。
In this article, approximations and inequalities for the distribution of a two dimensional scan statistic are derived for independently and identically distributed observations from a continuous distribution. The accuracy of these approximations and inequalities is investigated for a normal model. The cases of mean and variance being known and unknown are discussed. Based on approximations for the distributions of one and two dimensional fixed window scan statistics, variable window scan statistics are introduced. We investigate the performance of these variable window scan statistics as test statistics for detection of a local change in the mean of a normal distribution. By utilizing R algorithms for the multivariate normal and distributions established by Genz and Bretz (2009), numerical results are presented to evaluate the efficiency of implementing the variable window scan statistics and compare their performance, via power calculations, with fixed window scan statistics. It is evident from the numerical results that if the dimension of the window where a change has occurred is unknown, the variable window scan statistics outperform the fixed window scan statistics.
DOI：
10.1073/pnas.170179197
发表时间：
2000-08-15
影响因子：
11.1
作者：
Hoh, J;Ott, J
通讯作者：
Ott, J