A second order model for cylindrical data

被引：17

作者：

Anderson-Cook, CM ^{[1
]}

机构：

[1] Virginia Polytech Inst & State Univ, Dept Stat, Blacksburg, VA 24061 USA

来源：

JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION | 2000年 / 66卷 / 01期

关键词：

directional data; circular-linear; Fourier series; polar coordinates;

D O I：

10.1080/00949650008812011

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

Modeling cylindrical data, comprised of a linear component and a directional component, can be done using Fourier series expansions if we consider the conditional distribution of the linear component given the angular component. This paper presents the second order model which is a natural extension of the Mardia and Sutton (1978) first order model. This model can be parameterized either in polar or Cartesian coordinates, and allows for parameter estimation using standard multiple linear regression. Characteristic of the new model, how to compare the adequacy of the fit for first and second order models, and an example involving wind direction and temperature are presented.

引用

页码：51 / 65

页数：15