Fast and robust estimation of the multivariate errors in variables model. [PDF]
TEST, 2009 In the multivariate errors in variable models one wishes to retrieve a linear relationship of the form y = ß x + a, where both x and y can be multivariate. The variables y and x are not directly measurable, but observed with measurement error.
Croux, Christophe +2 more
core +5 more sources
Asymptotic normality of total least squares estimator in a multivariate errors-in-variables model [PDF]
Modern Stochastics: Theory and Applications, 2016 We consider a multivariate functional measurement error model $AX\approx B$. The errors in $[A,B]$ are uncorrelated, row-wise independent, and have equal (unknown) variances.
Alexander Kukush +1 more
doaj +4 more sources
Goodness-of-fit test in a multivariate errors-in-variables model [PDF]
Modern Stochastics: Theory and Applications, 2016 We consider a multivariable functional errors-in-variables model $AX\approx B$, where the data matrices A and B are observed with errors, and a matrix parameter X is to be estimated.
Alexander Kukush +1 more
doaj +3 more sources
Simulating model uncertainty of subgrid-scale processes by sampling model errors at convective scales [PDF]
Nonlinear Processes in Geophysics, 2020 Ideally, perturbation schemes in ensemble forecasts should be based on the statistical properties of the model errors. Often, however, the statistical properties of these model errors are unknown. In practice, the perturbations are pragmatically modelled
M. Van Ginderachter +6 more
doaj +4 more sources
Adjusted Likelihood Inference in an Elliptical Multivariate Errors-in-Variables Model [PDF]
Communications in Statistics - Theory and Methods, 2014 In this paper we obtain an adjusted version of the likelihood ratio test for errors-in-variables multivariate linear regression models. The error terms are allowed to follow a multivariate distribution in the class of the elliptical distributions, which has the multivariate normal distribution as a special case.
Melo, Tatiane F. N. +1 more
openaire +4 more sources
Fitting an Equation to Data Impartially
Mathematics, 2023 We consider the problem of fitting a relationship (e.g., a potential scientific law) to data involving multiple variables. Ordinary (least squares) regression is not suitable for this because the estimated relationship will differ according to which ...
Chris Tofallis
doaj +1 more source
Multivariate Sea Surface Prediction in the Bohai Sea Using a Data-Driven Model
Journal of Marine Science and Engineering, 2023 Data-driven predictions of marine environmental variables are typically focused on single variables. However, in real marine environments, there are correlations among different oceanic variables.
Song Hu +6 more
doaj +1 more source
Role of Management Earnings Forecast Error in Stock Market Efficiency with Emphasis on Earnings and Operation Earnings Components [PDF]
مجله دانش حسابداری, 2020 Objective: The purpose of this research was to investigate the role of management earnings forecast errors in stock market efficiency with emphasis on operation earnings and their components in the Tehran Stock Exchange from 2009 to 2017.
Shamsi Vahedi, Saeed Ali ahmadi (Ph.D)
doaj +1 more source
Prediction in polynomial errors-in-variables models
Modern Stochastics: Theory and Applications, 2020 A multivariate errors-in-variables (EIV) model with an intercept term, and a polynomial EIV model are considered. Focus is made on a structural homoskedastic case, where vectors of covariates are i.i.d. and measurement errors are i.i.d. as well.
Alexander Kukush, Ivan Senko
doaj +1 more source
K-Nearest Neighbor Method with Principal Component Analysis for Functional Nonparametric Regression
مجلة بغداد للعلوم, 2022 This paper proposed a new method to study functional non-parametric regression data analysis with conditional expectation in the case that the covariates are functional and the Principal Component Analysis was utilized to de-correlate the multivariate
Shelan Saied Ismaeel +2 more
doaj +1 more source