Least-squares variance component estimation

نویسندگان
چکیده

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Least-squares variance component estimation

Least-squares variance component estimation (LS-VCE) is a simple, flexible and attractive method for the estimation of unknown variance and covariance components. LS-VCE is simple because it is based on the well-known principle of LS; it is flexible because it works with a userdefined weight matrix; and it is attractive because it allows one to directly apply the existing body of knowledge of L...

متن کامل

Retrieving Three Dimensional Displacements of InSAR Through Regularized Least Squares Variance Component Estimation

Measuring the 3D displacement fields provide essential information regarding the Earth crust interaction and the mantle rheology. The interferometric synthetic aperture radar (InSAR) has an appropriate capability in revealing the displacements of the Earth’s crust. Although, it measures the real 3D displacements in the line of sight (LOS) direction. The 3D displacement vectors can be retrieved ...

متن کامل

Least-Squares Variance Component Estimation: Theory and GPS Applications

Data processing in geodetic applications often relies on the least-squares method, for which one needs a proper stochastic model of the observables. Such a realistic covariance matrix allows one first to obtain the best (minimum variance) linear unbiased estimator of the unknown parameters; second, to determine a realistic precision description of the unknowns; and, third, along with the distri...

متن کامل

​Rank based Least-squares Independent Component Analysis

  In this paper, we propose a nonparametric rank-based alternative to the least-squares independent component analysis algorithm developed. The basic idea is to estimate the squared-loss mutual information, which used as the objective function of the algorithm, based on its copula density version. Therefore, no marginal densities have to be estimated. We provide empirical evaluation of th...

متن کامل

Range Image Sequence Analysis by 2.5-d Least Squares Tracking with Variance Component Estimation and Robust Variance Covariance Matrix Estimation

In this article, a range image sequence tracking approach is proposed, which combines 3-D camera intensity and range observations in an integrated geometric transformation model. Based on 2-D least squares matching, a closed solution for intensity and range observations has been developed. By combining complementary information, an increase in accuracy and reliability can be achieved. The weigh...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: Journal of Geodesy

سال: 2007

ISSN: 0949-7714,1432-1394

DOI: 10.1007/s00190-007-0157-x