共查询到20条相似文献，搜索用时 31 毫秒
1.
非线性模型中方差和协方差分量的估计 总被引：5，自引：1，他引：4
采用差分代替微分的方法,并将非线性模型的似然函数分解为函数模型生成的似然函数和正交补似然函数(也是边缘似然函数)的乘积,由正交补似然函数得到非线性模型中严格的和简化的方差和协方差分量估计的迭代公式.很多学者提出的线性模型中方差和协方差分量估计的迭代公式都是本文的特殊情况. 相似文献
2.
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
3.
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
4.
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
5.
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
6.
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
7.
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
8.
Application of least squares variance component estimation to errors-in-variables models 总被引：3，自引：2，他引：1
A. R. Amiri-Simkooei 《Journal of Geodesy》2013,87(10-12):935-944
9.
WANG XinzhouLIU JingnanTAO BenzaoWANG Xinzhou Professor School of Geo-science Surveying Engineering WTUSM Wuhan China 《地球空间信息科学学报》1998,(1)
This paper studies the estimation of variance and covariance compo-nents for GPS baseline network by MINQUE method.The fundamental rule forselecting variance-covariance model has been presented,and the alternative algo-rithm which simultaneouly estimates fixed variance components and scalled vari-ance components of the distance,azimuth and geodetic height difference for a GPSbaseline vector has been developed. 相似文献
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方差分量的极大验后估计 总被引：4，自引：0，他引：4
由概括函数模型出发,导出了适应于所有平差模型的方差分量的极大验后估计,这种估计实际上是先验方差与样本方差的凸组合。文中还给出了一个简单的数例,说明这种方法的可行性。 相似文献
12.
In this contribution, using the example of the Mátern covariance matrices, we study systematically the effect of apriori fully populated variance covariance matrices (VCM) in the Gauss–Markov model, by varying both the smoothness and the correlation length of the covariance function. Based on simulations where we consider a GPS relative positioning scenario with double differences, the true VCM is exactly known. Thus, an accurate study of parameters deviations with respect to the correlation structure is possible. By means of the mean-square error difference of the estimates obtained with the correct and the assumed VCM, the loss of efficiency when the correlation structure is missspecified is considered. The bias of the variance of unit weight is moreover analysed. By acting independently on the correlation length, the smoothness, the batch length, the noise level, or the design matrix, simulations allow to draw conclusions on the influence of these different factors on the least-squares results. Thanks to an adapted version of the Kermarrec–Schön model, fully populated VCM for GPS phase observations are computed where different correlation factors are resumed in a global covariance model with an elevation dependent weighting. Based on the data of the EPN network, two studies for different baseline lengths validate the conclusions of the simulations on the influence of the Mátern covariance parameters. A precise insight into the impact of apriori correlation structures when the VCM is entirely unknown highlights that both the correlation length and the smoothness defined in the Mátern model are important to get a lower loss of efficiency as well as a better estimation of the variance of unit weight. Consecutively, correlations, if present, should not be neglected for accurate test statistics. Therefore, a proposal is made to determine a mean value of the correlation structure based on a rough estimation of the Mátern parameters via maximum likelihood estimation for some chosen time series of observations. Variations around these mean values show to have little impact on the least-squares results. At the estimates level, the effect of varying the parameters of the fully populated VCM around these approximated values was confirmed to be nearly negligible (i.e. a mm level for strong correlations and a submm level otherwise). 相似文献
13.
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
14.
When certain constraints in the kinematic state parameters of a multi-sensor navigation system exist, they should be taken
into account for the improvement of the positioning accuracy and reliability. In this paper, two types of robust estimators
for integrated and two stages of Kalman filtering with state parameter constraints are derived based on the generalized maximum
likelihood Lagrangian condition, respectively. The properties of the two estimators are discussed. The changes of the state
estimates and their covariance matrices as well as the residual vector caused by the constraints are derived and analyzed.
It is shown by a simulated example that the precision of the state estimates provided by the Kalman filtering with constraints
is better than that provided by the Kalman filtering without considering the state parameter constraints; and the robust Kalman
filtering with constraints further improves the reliability and robustness of the state estimates. 相似文献
15.
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
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全球定位系统/航位推算组合导航定位中,由于目标运动的不确定性,GPS接收机与DR器件接收的数据存在噪声,使预置目标运动模型通常很难得到较高跟踪精度,针对应用常规卡尔曼滤波进行组合导航解算由于噪声统计特性未知而引起滤波不稳定的问题,本文提出了一种基于新息序列的量测计算进行自适应估计的卡尔曼滤波算法。该算法通过对新息方差强度进行极大似然估计,将新息计算引入卡尔曼滤波器的增益计算,达到控制发散的目的。最后对改进的算法与一般卡尔曼滤波算法做了对比仿真试验分析,结果表明了改进算法的有效性。 相似文献
19.
大地测量相关观测抗差估计理论 总被引：21，自引：4，他引：21
相关观测异常诊断、质量控制是测量数据处理领域亟待解决的难题之一。分别从方差膨胀模型和相关权元素压缩模型入手研究了相关观测的质量控制理论和方法；给出了误差影响函数；构造了方差膨胀函数和权因子收缩函数；利用观测量的等价协方差阵和等价权矩阵讨论了相关观测质量控制的计算方法。该等价协方差矩阵和等价权矩阵不仅保持了原有协方差矩阵和权矩阵的对称性，而且保持了原有协方差矩阵的相关性不变。计算结果表明异常观测的方差膨胀法和等价权法能有效地控制异常观测对参数估值的影响。 相似文献
20.
G. Fotopoulos 《Journal of Geodesy》2005,79(1-3):111-123
The well-known statistical tool of variance component estimation (VCE) is implemented in the combined least-squares (LS) adjustment of heterogeneous height data (ellipsoidal, orthometric and geoid), for the purpose of calibrating geoid error models. This general treatment of the stochastic model offers the flexibility of estimating more than one variance and/or covariance component to improve the covariance information. Specifically, the iterative minimum norm quadratic unbiased estimation (I-MINQUE) and the iterative almost unbiased estimation (I-AUE) schemes are implemented in case studies with observed height data from Switzerland and parts of Canada. The effect of correlation among measurements of the same height type and the role of the systematic effects and datum inconsistencies in the combined adjustment of ellipsoidal, geoid and orthometric heights on the estimated variance components are investigated in detail. Results give valuable insight into the usefulness of the VCE approach for calibrating geoid error models and the challenges encountered when implementing such a scheme in practice. In all cases, the estimated variance component corresponding to the geoid height data was less than or equal to 1, indicating an overall downscaling of the initial covariance (CV) matrix was necessary. It was also shown that overly optimistic CV matrices are obtained when diagonal-only cofactor matrices are implemented in the stochastic model for the observations. Finally, the divergence of the VCE solution and/or the computation of negative variance components provide insight into the selected parametric model effectiveness. 相似文献