Results 21 to 30 of about 2,136,192 (344)
Consistency checks for particle filters [PDF]
, 2006 An "inconsistent" particle filter produces - in a statistical sense - larger estimation errors than predicted by the model on which the filter is based. Two test variables are introduced that allow the detection of inconsistent behavior.
Heijden, F. van der
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The Case of the Homogeneous Errors-In-Variables Model
Journal of Geodetic Science, 2014 Recently, it has been claimed that the HomogeneousErrors-In-Variables (HEIV) Model, where the lefthandside (LHS) vector is allowed to be multiplied withan unknown scale factor, would represent a generalizationof the regular EIV-Model for which a number ...
Schaffrin B., Snow K.
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Open Mathematics, 2020 In this article, an errors-in-variables regression model in which the errors are negatively superadditive dependent (NSD) random variables is studied. First, the Marcinkiewicz-type strong law of large numbers for NSD random variables is established. Then,
Zhang Yu +3 more
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A Mathematical Programming Approach for Integrated Multiple Linear Regression Subset Selection and Validation [PDF]
, 2020 Subset selection for multiple linear regression aims to construct a regression model that minimizes errors by selecting a small number of explanatory variables.
Cheong, Taesu +3 more
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A General Solution for the Errors in Variables (EIV) Model with Equality and Inequality Constraints
Applied Sciences, 2022 Targeting the adjustment of the errors-in-variables (EIV) model with equality and inequality constraints, a general solution that is similar to the classical least square adjustment is proposed based on the penalty function and the weight in measurement.
Dengshan Huang, Yulin Tang, Qisheng Wang
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Testing the suitability of polynomial models in errors-in-variables problems [PDF]
, 2007 A low-degree polynomial model for a response curve is used commonly in practice. It generally incorporates a linear or quadratic function of the covariate.
Hall, Peter, Ma, Yanyuan
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Errors-in-Variables Models [PDF]
, 2000 Errors-in-variables (EIV) models axe regression models in which the regres-sors axe observed with errors. These models include the linear EIV models, the nonlinear EIV models, and the partially linear EIV models. Suppose that we want to investigate the relationship between the yield (Y) of corn and available nitrogen (X) in the soil.
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On The Errors-In-Variables Model With Singular Dispersion Matrices
Journal of Geodetic Science, 2014 While the Errors-In-Variables (EIV) Model has been treated as a special case of the nonlinear Gauss- Helmert Model (GHM) for more than a century, it was only in 1980 that Golub and Van Loan showed how the Total Least-Squares (TLS) solution can be ...
Schaffrin B., Snow K., Neitzel F.
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Estimation of Nonlinear Errors-in-Variables Models
The Annals of Statistics, 1982 An estimation procedure is presented for the coefficients of the nonlinear functional relation, where observations are subject to measurement error. The distributional properties of the estimators are derived, and a consistent estimator of the covariance matrix is given.
Wolter, Kirk M., Fuller, Wayne A.
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Testing homogeneity in Weibull error in variables models [PDF]
Annals of the Institute of Statistical Mathematics, 2006 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Valença, Dione Maria, Bolfarine, Heleno
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