Abstract
The existence of orthogonal parameters to the mean is characterized by a partial differential equation involving the mean, the variance and the cumulant generating function. This condition allows to explain and construct orthogonal parametrizations in several cases of interest, including higher parametric ones.
Similar content being viewed by others
References
Amari, S. (1985). Differential Geometrical Methods in Statistics. Lecture Notes in Statistics 28, Springer Verlag, New York.
Cox, D., and Reid, N. (1987). Parameter Orthogonality and Approximate Conditional inference (with discussion). J.R. Statist. Soc. B 49, 1–39.
Hürlimann, W. (1990). On maximum likelihood estimation for count data models. Insurance: Mathematics and Economics 9, 39–49.
Huzurbazar, V. (1950). Probability distributions and orthogonal parameters. Proc. Camb. Phil. Soc. 46, 281–84.
Sprott, D. (1983). Estimating the parameters of a convolution by maximum likeli hood. Journal of the American Statistical Association 78, 457–60.
Tietjen, G.L. (1986). A Topical Dictionary of Statistics. Chapman and Hall.
Willmot, G.E. (1989). A remark on the Poisson-Pascal and some other contagious distributions. Statistics and Probability Letters 7, 217–20.
Willmot, G.E. (1990). On construction of a parameter orthogonal to the mean. Appears in Biometrika.
Author information
Authors and Affiliations
Rights and permissions
About this article
Cite this article
Hürlimann, W. On parameter orthogonality to the mean. Statistical Papers 33, 69–74 (1992). https://doi.org/10.1007/BF02925313
Received:
Revised:
Issue Date:
DOI: https://doi.org/10.1007/BF02925313