A statistical method to describe the relationship of circular variables simultaneously
Document Type
Article
Publication Date
1-1-2010
Abstract
This paper proposes a statistical model to compare or describe the relationship between several circular variables which are subjected to measurement errors. The model is known as the simultaneous linear functional relationship for circular variables and it is, in fact, an extension of the linear functional relationship model. Maximum likelihood estimation of parameters has been obtained iteratively by assuming that the ratios of concentration parameters are known and by choosing suitable initial values. In particular, an improved estimate of the concentration parameter is proposed. In addition, the variance and covariance of parameters have been derived using the Fisher information matrix. To illustrate the applicability of the model to real data, the relationship of the Malaysian wind direction data recorded at various levels is described.
Keywords
Simultaneous linear function relationship model, circular variables, von Mises distribution, concentration parameters, wind direction data
Publication Title
Pakistan Journal of Statistics
Volume
26
Issue
4
Publisher
ISOSS Publ
Publisher Location
PLOT 426, BLOCK J-3, M A JOHAR, LAHORE, 00000, PAKISTAN