共查询到17条相似文献,搜索用时 187 毫秒
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拟合推估两步极小解法 总被引:11,自引:1,他引:11
在回顾了最小二乘拟合推估的“综合极小”解法(正常拟合推估)后,分析了正常拟合推估存在的问题。考虑到随机场信号不一定完全表现为随机性,其中可能含有趋势性,顾而提出了拟合推估的“两步极小”解法,即将随机场分成趋势性部分和随机性部分,对趋势性部分采用函数拟合,对随机性部分采用协方差函数拟合。给出了“分两步极小”拟合推估的2种解法。计算表明,两步极小解法能部分地改善拟合推估的精度。 相似文献
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最小二乘插值与拟合推估 总被引:4,自引:1,他引:4
简述了最小二乘插值法的原理及解算过程 ,逐步引入最小二乘纯推估的概念 ,讨论了滤波与推估的结合 ,进而导出了最小二乘拟合推估的一般模型 ,得出了“最小二乘插值是拟合推估的特殊情况”的结论 ,对最小二乘拟合推估的解析性进行了简要的讨论 相似文献
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半参数模型与拟合推估模型的比较 总被引:8,自引:0,他引:8
在分析半参数模型与拟合推估模型的基础上,指出半参数模型可以包括拟合推估模型.在信号是随机量且其协方差矩阵已知时,通过选择合适的正则化参数,利用半参数模型可以改进拟合推估的结果.通过一个坐标变换的算例,比较这种情况下半参数模型和拟合推估模型的效果. 相似文献
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《测绘文摘》2002,(4)
CH20022751 拟合推估新解之一——两步解法/周江文(中国科学院测量与地球物理研究所)∥测绘学报.—2002,31(3).—189~191 拟合推估的一般模式,通常用双拟合法则(2)求解,它有一定的缺陷。提出一种解法,分为2步:(1)将Y项并入△,在单拟合下求X的优估值X;(2)把X项纳入L,Y作确定未知量,也在单拟合下求其估值Y。参4 CH20022752 拟合推估两步极小解法/杨元喜,刘念∥测绘学报.—2002,31(3).—192~195 在回顾了最小二乘拟合推估的“综合极小”解法(正常拟合推估)后,分析了正常拟合推估存在的问题。考虑到随机场信号不一定完全表现为随机性,其中可能含有趋势 相似文献
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基于各向异性的自适应拟合推估及其在缺失数据拟合中的应用 总被引:1,自引:0,他引:1
随机信号协方差函数的拟合和确定是拟合推估的关键。在常规拟合推估方法中, 通常认为随机信号具有各向同性, 而事实上各向异性现象却更为普遍。另外, 在拟合过程中, 很难保证信号协方差与观测噪声协方差的先验方差因子一致。基于此, 本文提出了基于变异函数的各向异性自适应拟合推估方法, 并将其应用于InSAR监测缺失数据的拟合。 相似文献
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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
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Least squares adjustment and collocation 总被引:10,自引:1,他引:10
K. -R. Koch 《Journal of Geodesy》1977,51(2):127-135
Summary For the estimation of parameters in linear models best linear unbiased estimates are derived in case the parameters are random
variables. If their expected values are unknown, the well known formulas of least squares adjustment are obtained. If the
expected values of the parameters are known, least squares collocation, prediction and filtering are derived. Hence in case
of the determination of parameters, a least squares adjustment must precede a collocation because otherwise the collocation
gives biased estimates. Since the collocation can be shown to be equivalent to a special case of the least squares adjustment,
the variance of unit weight can be estimated for the collocation also. This estimate gives the scale factor for the covariance
matrices being used in the collocation. In addition, the methods of testing hypotheses and establishing confidence intervals
for the parameters of the least squares adjustment may be applied to the collocation. 相似文献
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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
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张亮 《测绘与空间地理信息》2008,31(2):145-148
抗差估计具有较好的抗拒异常观测值及粗差的能力,而最小二乘配置又能较好地处理系统误差,本文结合两者的优点,利用抗差最小二乘配置对数字化地图进行几何纠正,其中对协方差函数采用抗差拟合,得到了较好的结果。实验证明在GIS数据处理的扫描数字化地图几何纠正中,抗差最小二乘配置在抗拒异常值和处理系统误差方面优于单纯的最小二乘估计和单纯的最小二乘配置方法。 相似文献
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The least squares collocation algorithm for estimating gravity anomalies from geodetic data is shown to be an application
of the well known regression equations which provide the mean and covariance of a random vector (gravity anomalies) given
a realization of a correlated random vector (geodetic data). It is also shown that the collocation solution for gravity anomalies
is equivalent to the conventional least-squares-Stokes' function solution when the conventional solution utilizes properly
weighted zero a priori estimates. The mathematical and physical assumptions underlying the least squares collocation estimator
are described. 相似文献