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CO-REGISTRATION OF 3D POINT CLOUDS BY USING AN ERRORS-IN-VARIABLES MODEL [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2012 Co-registration of point clouds of partially scanned objects is the first step of the 3D modeling workflow. The aim of co-registration is to merge the overlapping point clouds by estimating the spatial transformation parameters. In the literature, one of
U. Aydar +3 more
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Self-Consistent Density Estimation in the Presence of Errors-in-Variables
Abstract and Applied Analysis, 2014 This paper considers the estimation of the common probability density of independent and identically distributed variables observed with additive measurement errors.
Junhua Zhang, Yuping Hu, Sanying Feng
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Journal of Inequalities and Applications, 2020 In this paper, we estimate the mean of the partially linear single-index errors-in-variables model with missing response variables. The linear covariate is measured with additive error, therefore missing is not random.
Xin Qi, ZhuoXi Yu
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Vestnik Samarskogo Gosudarstvennogo Tehničeskogo Universiteta. Seriâ: Fiziko-Matematičeskie Nauki, 2011 The recursive algorithm allowing to receive strongly consistent estimates of parameters of multidimensional on an input linear dynamic systems with locally autocorrelated noise in input and output signals is suggested.
Dmitriy V Ivanov, Oleg A Katsyuba
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NeuroImage, 2020 Comparing electric field simulations from individualized head models against in-vivo intra-cranial recordings is considered the gold standard for direct validation of computational field modeling for transcranial brain stimulation and brain mapping ...
Oula Puonti +3 more
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On the Interpretation of Instrumental Variables in the Presence of Specification Errors
Econometrics, 2015 The method of instrumental variables (IV) and the generalized method of moments (GMM), and their applications to the estimation of errors-in-variables and simultaneous equations models in econometrics, require data on a sufficient number of instrumental ...
P.A.V.B. Swamy +2 more
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Scaled weighted total least-squares adjustment for partial errors-in-variables model
Journal of Geodetic Science, 2016 Scaled total least-squares (STLS) unify LS, Data LS, and TLS with a different choice of scaled parameter. The function of the scaled parameter is to balance the effect of random error of coefficient matrix and observation vector for the estimate of ...
Zhao J.
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Geomatics, Natural Hazards & Risk, 2020 A difficulty in variance component estimation (VCE) is that the estimates may become negative, which is not acceptable in practice. This article presents two new methods for non-negative VCE that utilize the expectation maximization algorithm for the ...
Leyang Wang, Qiwen Wu
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Factors determining the forecast errors of market analysts for fiscal variables in Brazil
RACE: Revista de Administração, Contabilidade e Economia, 2020 The objective of this study is to investigate determinant factors the forecast errors of market analysts for Brazilian fiscal variables. The data for conducting the research was obtained in the Prisma Fiscal, the Ministry of Economy's system of ...
Francisca Aparecida de Souza +2 more
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Algorithms and statistical analysis for linear structured weighted total least squares problem
Geodesy and GeodynamicsWeighted total least squares (WTLS) have been regarded as the standard tool for the errors-in-variables (EIV) model in which all the elements in the observation vector and the coefficient matrix are contaminated with random errors.
Jian Xie +4 more
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