从测量误差的实际情况出发,提出一元非对称P范分布极大似然平差方法,建立该方法的数学模型,得到一元非对称P范分布的密度函数,利用极大似然估计方法推导参数估计值的基础方程。研究表明,结合实际测量数据,通过选择合适的参数估计值,可以增加误差分布模型选取的灵活性,便于P范分布理论在测绘数据处理中的推广应用。
According to the foundational properties of the random errors,this paper deduces a more general error distribution—the unsymmetrical P-norm distribution,and then discusses the maximum likelihood adjustment of the p-norm distribution in detail.The distributions of degenerate,Laplace,normal and rectangular are the specific cases of the unsymmetrical P-norm distribution respectively.The maximum likelihood adjustment method of the unsymmetrical P-norm distribution is proposed,and the foundational equations of the adjustment are given.For each concrete measuring data,It can be selected that a suitable value to be more close to the real one of the error than the normal distribution is.The method is the further generalization of the one of maximum likelihood adjustment of the P-norm distribution.