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Some Angular-Linear Distributions and Related Regression Models
Richard A. Johnson and Thomas E. Wehrly
Journal of the American Statistical Association
Vol. 73, No. 363 (Sep., 1978), pp. 602-606
Stable URL: http://www.jstor.org/stable/2286608
Page Count: 5
You can always find the topics here!Topics: Sine function, Regression analysis, Entropy, Statistical models, Maximum likelihood estimators, Linear regression, Gaussian distributions, Parametric models, Distributivity, Least squares
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Parametric models are proposed for the joint distribution of bivariate random variables when one variable is directional and one is scalar. These distributions are developed on the basis of the maximum entropy principle and by the specification of the marginal distributions. The properties of these distributions and the statistical analysis of regression models based on these distributions are explored. One model is extended to several variables in a form that justifies the use of least squares for estimation of parameters, conditional on the observed angles.
Journal of the American Statistical Association © 1978 American Statistical Association