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Applying Monte Carlo Method for Straight-Line Model Sensor Calibration [PDF]
SensorsSensors are used in measurement systems to enable estimation of physical parameters. Their calibration is an essential requirement and to perform the overall system/sensor calibration, its input is changed while the output is measured. Parameters from an
Pedro M. Ramos, Fernando M. Janeiro
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Bartlett and Bartlett-type corrections in heteroscedastic symmetric nonlinear regression models [PDF]
Anais da Academia Brasileira de Ciências, 2022 This paper provides general expressions for Bartlett and Bartlett-type correction factors for the likelihood ratio and gradient statistics to test the dispersion parameter vector in heteroscedastic symmetric nonlinear models.
MARIANA C. ARAÚJO +2 more
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Журнал Белорусского государственного университета: Математика, информатика, 2020 In article the problem of construction continuous (number of observations is not fixed) D-optimal designs of experiments for trigonometric regression in a case when variance of errors of observations depend on a point in which is made is investigated ...
Valery P. Kirlitsa
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Correlation Based Ridge Parameters in Ridge Regression with Heteroscedastic Errors and Outliers [PDF]
Journal of Statistical Theory and Applications (JSTA), 2015 This paper introduces some new estimators for estimating ridge parameter, based on correlation between response and regressor variables for ridge regression analysis.
A.V. Dorugade
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Corrected score estimators in linear multivariate multiple regression models with heteroscedastic measurement errors [PDF]
Songklanakarin Journal of Science and Technology (SJST), 2018 In this study, the knowledge of estimation theory based on the corrected score (CS) approach is extended in a linear multivariate multiple regression model with heteroscedastic measurement errors (HMEs) and an unknown HME variance.
Wannaporn Junthopas +2 more
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D-optimal experimental designs for linear multiple regression under heteroscedastic observations
Журнал Белорусского государственного университета: Математика, информатика, 2020 The problem of construction of «continuous» (number of observations is not fixed) and «exact» (number of observations is fixed) D-optimal experimental designs for linear multiple regression in the case when variance of errors of observations depends on ...
Valery P. Kirlitsa
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Remote Sensing, 2020 The choice of an appropriate metric is mandatory to perform deformation analysis between two point clouds (PC)—the distance has to be trustworthy and, simultaneously, robust against measurement noise, which may be correlated and heteroscedastic ...
Gaël Kermarrec +2 more
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Forecasting emergency department arrivals using INGARCH models
Health Economics Review, 2023 Background Forecasting patient arrivals to hospital emergency departments is critical to dealing with surges and to efficient planning, management and functioning of hospital emerency departments.
Juan C. Reboredo +3 more
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Autoregressive Models with Time-Dependent Coefficients—A Comparison between Several Approaches
Stats, 2022 Autoregressive-moving average (ARMA) models with time-dependent (td) coefficients and marginally heteroscedastic innovations provide a natural alternative to stationary ARMA models. Several theories have been developed in the last 25 years for parametric
Rajae Azrak, Guy Mélard
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Entropy, 2020 In this study, we consider an online monitoring procedure to detect a parameter change for integer-valued generalized autoregressive heteroscedastic (INGARCH) models whose conditional density of present observations over past information follows one ...
Sangyeol Lee, Dongwon Kim
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