共查询到18条相似文献，搜索用时 140 毫秒
1.
国际著名大地测量和摄影测量学家、澳大利亚昆士兰大学空间卫星导航中心工程博士K·库比克教授和国际著名大地和工程测量学家、联邦德国慕尼黑国防军大学工程博士W·威尔施教授,最近对武汉测绘科技大学教授、博士导师於宗俦所撰写的两篇论文《方差——协方差分量估计的统一理论》和《方差——协方差分量极大似然估计的通用公式》作了高度评价,现将他们的全文翻译于下。库比教授是这样评论的: 我想对於宗俦教授所写的论文《方差——协方差分量估计的统一理论》、《方差——协方差分量极大似然估计的通用公式》作一些评论。 方差分量的各种各样估计方法,如极大似然估计(ML)、最优二次无偏估计(BQUE)以及最小范数二次无偏估计(MINQUE)等等,是统计学家哈列(Hartley)和劳(Rao)所开创的(1967,1973)。从这以后,在这一领域内进行了大量的研究。然而,总的说来,统计学家是致力于误差向量的结构以及以一般模型为基础的估计量特性的研究上。而测量学家们则把他们的注意力局限于函数模型的结构上,这些模型是随着应用上的不同而变化很大。 相似文献
2.
GIS叠置图层方差分量的极大似然估计 总被引：1，自引：0，他引：1
针对GIS叠置中的同名点,以维希特分布密度为似然函数,提出了各图层方差分量的极大似然估计方法。该方法不依赖残差,不需要迭代就能估计未知参数和方差分量。 相似文献
3.
方差—协方差分量极大似然估计的通用公式 总被引：6，自引：1，他引：6
本文由概括平差函数模型出发，按极大似然做估计原则导出了适用于所有平差函数模型的方差分量估计的通用公式，由Ｋ．Ｋｕｂｉｋ和Ｃ．Ｒ．Ｋｏｃｈ所导出的两个公式都是它的特例。 相似文献
4.
方差分量估计的通用公式 总被引：1，自引：0，他引：1
应用最小二乘原理将方差分量估计公式从参数平差模型推广到概括函数平差模型。通过选取恰当的权阵,基于概括函数模型的最小范数二次无偏估计及赫尔默特法得到的公式均是本文的特例。视协方差矩阵为权逆阵,得到了最小方差估计,并证明了该公式与最优二次无偏估计的通用公式等价,从而表明最优二次无偏估计和极大似然估计的通用公式也是本文的特例。除此之外,本文还给出了最小二乘方差分量估计的简化公式,并对其进行了扩展。最小二乘方差分量估计的假设检验理论同样得到了推广。 相似文献
5.
基于方差分量估计的拟合推估及其在GIS误差纠正的应用 总被引：2，自引：0，他引：2
拟合推估解算必须首先求得信号向量的方差协方差矩阵,该协方差矩阵一般通过选定的协方差函数,并通过已测点数据进行拟合得到。显然观测噪声的先验方差协方差阵与拟合得到的随机信号的方差协方差矩阵必须相互协调,即观测噪声向量和信号向量的权矩阵所对应的方差因子应该一致,否则将对固定效应和随机效应参数的估计带来系统性的影响。应用方差分量估计来协调拟合推估模型中观测噪声和信号向量的随机模型,并分别从极大似然估计、MINQUE估计、赫尔默特方差分量估计三方面构建了拟合推估模型的方差分量解,最后利用新提出的理论与方法,对一幅实际的扫描地形图进行误差纠正,结果表明基于方差分量估计的拟合推估法能够提高扫描地形图的精度。 相似文献
6.
本文采用方差-协方差分量估计分析GPS残差时间序列噪声特性。介绍了该方法如何运用于GPS时间序列分析,详细的推导了函数模型,建立了数据处理流程。对比传统的极大似然估计,该方法可以定量计算各噪声分量的大小,并且具有计算速度快,数学模型严谨等优点。 相似文献
7.
於宗俦 《武汉大学学报(信息科学版)》1991,(2)
本文在概括函数模型和它的通用公式的基础上,导出了一个适用于所有平差方法的方差—协方差分量估计的通用公式,并由此给出方差分量估计的通用公式和简化的通用公式。 相似文献
8.
在多类观测数据联合平差中,存在某类观测值的验前协方差阵正确而其他类不正确的情况,传统Helmert方差分量估计在求解此类问题时没有对正确的验前协方差阵加以区别,从而造成正确的随机模型经估计后同样也被调整.针对上述情况,首先分析了Helmert方差分量估计迭代收敛结果的实质,然后提出了随机模型基准的概念,并推导了基于随机模型基准的Helmert方差分量估计公式.经计算表明,新公式完全可行,可以用于解决实际问题. 相似文献
9.
针对Partial EIV模型的方差分量估计中未考虑参数估值偏差所带来的影响,将Partial EIV模型视为非线性函数得到参数估值的偏差及二阶近似协方差表达式,计算得到偏差改正后的参数估值,结合方差分量估计方法,更新由参数估值影响的矩阵变量,给出了基于偏差改正的方差分量估计迭代方法。试验结果表明,参数估值及其协方差主要受参数估值偏差大小的影响,加入偏差改正能够得到更加合理的参数估值及方差分量估值,偏差改正后的方差分量估值可更加合理地评估参数估值的精度信息。 相似文献
10.
《测绘文摘》2008,(4)
CH20081939基于方差分量估计的拟合推估及其在GIS误差纠正的应用=Variance Component Estimation Based Collocation and Its Application in GIS Error Fitting/杨元喜,张菊清,张亮(西安测绘研究所)//测绘学报.-2008,37(2).-152～157拟合推估解算必须首先求得信号向量的方差协方差矩阵,该协方差矩阵一般通过选定的协方差函数,并通过已测点数据进行拟合得到。显然观测噪声的先验方差协方差阵与拟合得到的随机信号的方差协方差矩阵必须相互协调,即观测噪声向量和信号向量的权矩阵所对应的方差因子应该一致,否则将对固定效应和随机效应参数的估计带来系统性的影响。应用方差分量估计来协调拟合推估模型中观测噪声和信号向量的随机模型,并分别从极大似然估计、MINQUE估计、赫尔默特方差分量估计三方面构建了拟合推估模型的方差分量解,最后利用新提出的理论与方法,对一幅实际的扫描地形图进行误差纠正,结果表明基于方差分量估计的拟合推估法能够提高扫描地形图的精度。图2表1参22 相似文献
11.
Maximum likelihood estimate of variance components 总被引：2，自引：6，他引：2
Summary Using the orthogonal complement likehood function, an iterative procedure for the maximum likelihood estimates of the variance
and covariance components is derived. It is shown that these estimates are identical with the reproducing estimates of the
locally best invariant quadratic unbiased estimation of variance and covariance components. Successive approximations of the
maximum likelihood estimates are given in addition. 相似文献
12.
Estimation of variance and covariance components 总被引：3，自引：2，他引：3
Ou Ziqiang 《Journal of Geodesy》1989,63(2):139-148
13.
Estimability analysis of variance and covariance components 总被引：1，自引：1，他引：1
Although variance and covariance components have been extensively investigated and a number of elegant formulae to compute
them have been derived, nothing is known, without any ambiguity, about their estimability in the case of a fully unknown variance–covariance
matrix. We prove that variance and covariance components in this case are not estimable, thus clarifying the ambiguity of
the literature on the topic and correcting some erroneous statements in the literature. We also give a new theorem on the
estimability of a linear function of variance and covariance components. Then we propose a new method to estimate the variance–covariance
matrix with special structure, which can presumably be represented by, at most, r(r + 1)/2 independent parameters to guarantee its estimability in such a subspace, by directly implementing the positive definiteness
of the matrix as constraint to the restricted maximum likelihood method, where r is the number of redundant measurements. Therefore, our estimates of the variance and covariance components always reconstruct
a positive definite matrix and are always physically meaningful. 相似文献
14.
In collocation applications, the prior covariance matrices or weight matrices between the signals and the observations should
be consistent to their uncertainties; otherwise, the solution of collocation will be distorted. To balance the covariance
matrices of the signals and the observations, a new adaptive collocation estimator is thus derived in which the corresponding
adaptive factor is constructed by the ratio of the variance components of the signals and the observations. A maximum likelihood
estimator of the variance components is thus derived based on the collocation functional model and stochastic model. A simplified
Helmert type estimator of the variance components for the collocation is also introduced and compared to the derived maximum
likelihood type estimator. Reasonable and consistent covariance matrices of the signals and the observations are arrived through
the adjustment of the adaptive factor. The new adaptive collocation with related adaptive factor constructed by the derived
variance components is applied in a transformation between the geodetic height derived by GPS and orthometric height. It is
shown that the adaptive collocation is not only simple in calculation but also effective in balancing the contribution of
observations and the signals in the collocation model. 相似文献
15.
在多类观测数据联合平差中,存在某类观测值的验前协方差阵正确而其他类不正确的情况,传统Helmert方差分量估计在求解此类问题时没有对正确的验前协方差阵加以区别,从而造成正确的随机模型经估计后同样也被调整。针对上述情况,首先分析了Helmert方差分量估计迭代收敛结果的实质,然后提出了随机模型基准的概念,并推导了基于随机模型基准的Helmert方差分量估计公式。经计算表明,新公式完全可行,可以用于解决实际问题。 相似文献
16.
Khosro Moghtased-Azar Ramin Tehranchi Ali Reza Amiri-Simkooei 《Journal of Geodesy》2014,88(5):427-439
A typical problem of estimation principles of variance and covariance components is that they do not produce positive variances in general. This caveat is due, in particular, to a variety of reasons: (1) a badly chosen set of initial variance components, namely initial value problem (IVP), (2) low redundancy in functional model, (3) an improper stochastic model, and (4) data’s possibility of containing outliers. Accordingly, a lot of effort has been made in order to design non-negative estimates of variance components. However, the desires on non-negative and unbiased estimation can seldom be met simultaneously. Likewise, in order to search for a practical non-negative estimator, one has to give up the condition on unbiasedness, which implies that the estimator will be biased. On the other hand, unlike the variance components, the covariance components can be negative, so the methods for obtaining non-negative estimates of variance components are not applicable. This study presents an alternative method to non-negative estimation of variance components such that non-negativity of the variance components is automatically supported. The idea is based upon the use of the functions whose range is the set of all positive real numbers, namely positive-valued functions (PVFs), for unknown variance components in stochastic model instead of using variance components themselves. Using the PVF could eliminate the effect of IVP on the estimation process. This concept is reparameterized on the restricted maximum likelihood with no effect on the unbiasedness of the scheme. The numerical results show the successful estimation of non-negativity estimation of variance components (as positive values) as well as covariance components (as negative or positive values). 相似文献
17.
Simplified formulae for the BIQUE estimation of variance components in disjunctive observation groups 总被引：7，自引：1，他引：6
General rigorous and simplified formulae are reported for the best invariant quadratic unbiased estimates of the variance–covariance
components, which can be applied to all least-squares adjustments with the general linear stochastic model. Simplified procedures
are given for two cases frequently recurring in geodetic applications: uncorrelated groups of correlated or uncorrelated observations,
with more than one variance component in each group.
Received: 19 November 1998 / Accepted: 21 March 2000 相似文献