Results 1 to 10 of about 1,735,733 (226)
Errors-in-variables models: a generalized functions approach [PDF]
, 2009 Identification in errors-in-variables regression models was recently extended to wide models classes by S. Schennach (Econometrica, 2007) (S) via use of generalized functions. In this paper the problems of non- and semi- parametric identification in such models are re-examined.
Victoria Zinde‐Walsh
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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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Investigation of the Adaptivity Degree of State Variables in Linear Models of Dynamic Systems [PDF]
SensorsThis study investigates the concept of the adaptability degree of state variables in mathematical models used in estimation algorithms. Two numerical criteria are proposed for calculating the adaptability degree of state variables in linear models ...
Maria Selezneva +2 more
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ROBUST ESTIMATORS OF ERRORS-IN-VARIABLES MODELS, PART 1 [PDF]
SSRN Electronic Journal, 2004 It is well known that consistent estimators of errors-in-variables models require knowledge of the ratio of error variances. What is not well known is that a Joint Least Squares estimator is robust to a wide misspecification of that ratio. Through a series of Monte Carlo experiments we show that an easy-to-implement estimator produces estimates that ...
Quirino Paris, Paris, Quirino
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Errors-in-Variables Modeling of Personalized Treatment-Response Trajectories [PDF]
IEEE Journal of Biomedical and Health Informatics, 2020 Estimating the effect of a treatment on a given outcome, conditioned on a vector of covariates, is central in many applications. However, learning the impact of a treatment on a continuous temporal response, when the covariates suffer extensively from measurement error and even the timing of the treatments is uncertain, has not been addressed.
Guangyi Zhang +4 more
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Specification testing for errors-in-variables models [PDF]
Econometric Theory, 2016 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 ...
Taisuke Otsu, Luke Taylor
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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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Exploring the relationship between temperature forecast errors and Earth system variables [PDF]
Earth System Dynamics, 2022 Accurate subseasonal weather forecasts, from 2 weeks up to a season, can help reduce costs and impacts related to weather and corresponding extremes. The quality of weather forecasts has improved considerably in recent decades as models represent more ...
M. Ruiz-Vásquez +10 more
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Identification of Fractional Models of an Induction Motor with Errors in Variables
Fractal and Fractional, 2023 The skin effect in modeling an induction motor can be described by fractional differential equations. The existing methods for identifying the parameters of an induction motor with a rotor skin effect suggest the presence of errors only in the output ...
Dmitriy Ivanov
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Testing straightness of line objects using total least squares [PDF]
Tehnika, 2017 The paper presents the adaptation (fitting) of a set of points, with an estimated two-dimensional positions, to the straight line model of the by the application of the Weighted Total Least Squares, WTLS.
Popović Jovan +4 more
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