Cerrito P B
Department of Mathematics, University of Louisville, Kentucky 40292.
Math Biosci. 1991 Sep;106(1):23-37. doi: 10.1016/0025-5564(91)90038-k.
There are many statistical techniques that require the assumption that the population being studied is normally distributed--regression analysis, multivariate analysis, time series analysis, and so on. Unfortunately, as the development of survey sampling has long acknowledged, large human populations are usually stratified into several different subpopulations. Since the boundaries between the strata are somewhat blurred, they are not independent, so the overall distribution of the population tends to be multimodal rather than normal. In this paper, a technique is developed to find these multimodal techniques using nonparametric density estimation. Its effectiveness is demonstrated by means of an example.
有许多统计技术需要假设所研究的总体呈正态分布——回归分析、多变量分析、时间序列分析等等。不幸的是，正如长期以来调查抽样的发展所承认的那样，大量人群通常会被分层为几个不同的亚群体。由于各层之间的界限有些模糊，它们并非相互独立，因此总体的整体分布往往是多峰的而非正态的。在本文中，开发了一种使用非参数密度估计来找到这些多峰分布的技术。通过一个例子证明了其有效性。
