Saddlepoint approximations for some models of circular data
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- 作者：Riccardo Gatto ; Michael Mayer
- 关键词：Circular normal distribution ; Concentration parameter ; Locally most powerful test ; Normal and large deviation regions ; Power function ; Random walk ; Test of uniformity ; Wrapped symmetric ; none ; color ; black"" href
- 刊名：Statistical Methodology
- 出版年：2005
- 出版时间：December 2005
- 年：2005
- 卷：2
- 期：4
- 页码：233-248
- 全文大小：660 K
文摘
In this article we provide saddlepoint approximations for some important models of circular data. The particularity of these saddlepoint approximations is that they do not require solving the saddlepoint equation iteratively, so their evaluation is immediate. We first give very accurate approximations to P-values, critical values and power functions for some optimal tests regarding the concentration parameter under wrapped symmetric α-stable and circular normal models. Then, we consider an approximation to the distribution of a projection of the two-dimensional Pearson random walk with exponential step sizes.