Statistical Properties of the Unsymmetrical P-Norm Distribution


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The distribution of observation errors is determined according to their magnitudes by using the distribution collocation test method or figure method taking into account the result, sample total, the interval density etc. It is therefore difficult to get the specific type of error distribution of observations by conventional methods. In analyzing the actual situation of the observation error distribution using their statistical properties, this paper proposes the use of unsymmetrical distribution to express the true distribution of the observation errors. The P-norm distribution is a generalized form of a group of error distributions, and from the statistical properties of random errors we can arrive at an unsymmetrical P-norm distribution according to the practical situation of the occurrence of random errors. The common P-norm distribution is the specific case of this distribution. This paper deduces the density function equation of the unsymmetrical P-norm distribution, obtained the statistical properties of the distribution function and the evaluation of precision index. By choosing appropriate value for p, we can get closer to the distribution function of the true error distribution.



Key Engineering Materials (Volumes 439-440)

Edited by:

Yanwen Wu




P. Xiong et al., "Statistical Properties of the Unsymmetrical P-Norm Distribution", Key Engineering Materials, Vols. 439-440, pp. 1153-1158, 2010

Online since:

June 2010




[1] Sun Haiyan. Theory of P-norm distribution and application of surveying data processing. Wuhan: Wuhan Technical University of Surveying and Mapping, (1995).

[2] Zhou Jiangwen. Robust Estimation Essays. Beijing: Surveying and Mapping Press. (1990).

[3] Hu Hongchang, Sun Haiyan. The parameters estimation of P-norm distribution. Geomatics and Information Science of Wuhan University, 36(5), (2005), pp.483-484.

[4] A K Nandi, D Mämpel. An Extension of the Generalized Gaussian Distribution to Include Asymmetry. Journal of the Franklin Institute, 1(1995), pp.67-75.


[5] Sun Haiyan. Maximum Likelihood Adjustment of the monadic P-norm, Wuhan Technical University of Surveying and Mapping, 16(994), pp.150-156.

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