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CO-REGISTRATION OF 3D POINT CLOUDS BY USING AN ERRORS-IN-VARIABLES MODEL
Laser scanning point cloud registration matching estimation
2014/4/28
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 spatia...
Improved maximum likelihood estimators in a heteroskedastic errors-in-variables model
Bias correction errors-in-variables model maximum likelihoodestimation heteroskedastic model
2010/3/18
This paper develops a bias correction scheme for a multivariate heteroskedastic
errors-in-variables model. The applicability of this model is justified in
areas such as astrophysics, epidemiology an...
When a regression model is applied as an approximation of underlying model of data, the model checking is important and relevant. In this paper, we investigate the lack-of-fit test for a polynomial er...
Some Properties of A Lack-of-Fit Test for a Linear Errors in Variables Model
Linear errors-in-variables model model checking conditional expectation weight score test
2007/12/11
The relationship between the linear errors-in-variables model and the corresponding ordinary linear model in statistical inference is studied. It is shown that normality of the distribution of covaria...
This paper addresses estimation and its asymptotics of meantransformation $\theta=E[h(X)]$ of a random variable $X$ based on$n$ iid. observations from errors-in-variables model $ Y=X+~v $,where $v$ is...
Errors in Variables and Seasonal Ad justment Procedures
Signal extraction Measurement error Unob-served-components model Current Population Survey Un-employment rate
2014/3/18
Seasonal adjustment procedures attempt to estimate the sample realizations of an unobservable economic time series in the presence of both seasonal and irregular factors. In thi...