Results 11 to 20 of about 2,080 (215)
Dynamic Error-in-variables Models
Austrian Journal of Statistics, 2016 Several environmental problems are described by models defined by systems of first order differential equations. Typically, the derivatives of concentrations are expressed as functions of independent variables such as temperature, pressure, pH, etc ...
Vincenzo G. Dovì
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SPECIFICATION TESTING FOR ERRORS-IN-VARIABLES MODELS [PDF]
Econometric Theory, 2020 This paper considers specification testing for regression models with errors-in-variables and proposes a test statistic comparing the distance between the parametric and nonparametric fits based on deconvolution techniques. In contrast to the methods proposed by Hall and Ma (2007, Annals of Statistics, 35, 2620–2638) and Song (2008, Journal of ...
Otsu, Taisuke, Taylor, Luke Nicholas
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Errors-in-variables beta regression models [PDF]
Journal of Applied Statistics, 2014 Beta regression models provide an adequate approach for modeling continuous outcomes limited to the interval (0, 1). This paper deals with an extension of beta regression models that allow for explanatory variables to be measured with error. The structural approach, in which the covariates measured with error are assumed to be random variables, is ...
Carrasco, J. +2 more
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Error-in-variables modelling for operator learning.
Proposed for presentation at the MSML22 in ,, 2022 Deep operator learning has emerged as a promising tool for reduced-order modelling and PDE model discovery. Leveraging the expressive power of deep neural networks, especially in high dimensions, such methods learn the mapping between functional state variables. While proposed methods have assumed noise only in the dependent variables, experimental and
Ravi G. Patel +3 more
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Safety Analysis of the Patch Load Resistance of Plate Girders: Influence of Model Error and Variability [PDF]
Civil Engineering Infrastructures Journal, 2013 This study aims to undertake a statistical study to evaluate the accuracy of nine models that have been previously proposed for estimating the ultimate resistance of plate girders subjected to patch loading.
Farzad Shahabian +2 more
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Interdisciplinary Journal of Epidemiology and Public Health, 2021 Objective: To find a model of prediction of the medical cost of a Health Benefits Management Company (EAPB) with adequate statistical criteria. Methods: A Cross-sectional study with retrospective follow-up of the use of health services in an EAPB ...
Rodolfo Herrera Medina +2 more
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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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Barometr Regionalny, 2016 In this study, the effectiveness of classical regression models to forecast the indicator of mass accumulation of waste was investigated. The economic and infrastructural variables were used as explanatory variables.
Tomasz Szul, Krzysztof Nęcka
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A likelihood framework for deterministic hydrological models and the importance of non-stationary autocorrelation [PDF]
Hydrology and Earth System Sciences, 2019 The widespread application of deterministic hydrological models in research and practice calls for suitable methods to describe their uncertainty. The errors of those models are often heteroscedastic, non-Gaussian and correlated due to the memory ...
L. Ammann +4 more
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Energies, 2016 This paper presents novel intraday session models for price forecasts (ISMPF models) for hourly price forecasting in the six intraday sessions of the Iberian electricity market (MIBEL) and the analysis of mean absolute percentage errors (MAPEs) obtained ...
Claudio Monteiro +3 more
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