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Journal of Probability and Statistics, 2018 The analysis of misspecification was extended to the recently introduced stochastic restricted biased estimators when multicollinearity exists among the explanatory variables. The Stochastic Restricted Ridge Estimator (SRRE), Stochastic Restricted Almost
Manickavasagar Kayanan +1 more
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Stochastic Development Regression on Non-Linear Manifolds [PDF]
, 2017 We introduce a regression model for data on non-linear manifolds. The model describes the relation between a set of manifold valued observations, such as shapes of anatomical objects, and Euclidean explanatory variables.
EP Hsu +15 more
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New Stochastic Restricted Biased Regression Estimators
MathematicsIn this paper, we propose three stochastic restricted biased estimators for the linear regression model. These new estimators generalize the least squares estimator, mixed estimator, and biased estimator. We derive the necessary and sufficient conditions
Issam Dawoud, Hussein Eledum
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Nonlinear stochastic modelling with Langevin regression [PDF]
Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, 2021 Many physical systems characterized by nonlinear multiscale interactions can be modelled by treating unresolved degrees of freedom as random fluctuations. However, even when the microscopic governing equations and qualitative macroscopic behaviour are known, it is often difficult to derive a stochastic model that is consistent with observations.
J. L. Callaham +3 more
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Evaluation of Mutual Information and Feature Selection for SARS-CoV-2 Respiratory Infection
Bioengineering, 2023 This study aims to develop a predictive model for SARS-CoV-2 using machine-learning techniques and to explore various feature selection methods to enhance the accuracy of predictions. A precise forecast of the SARS-CoV-2 respiratory infections spread can
Sekar Kidambi Raju +6 more
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Granular Elastic Network Regression with Stochastic Gradient Descent
Mathematics, 2022 Linear regression is the use of linear functions to model the relationship between a dependent variable and one or more independent variables. Linear regression models have been widely used in various fields such as finance, industry, and medicine.
Linjie He +3 more
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A New Lifetime Model, Stochastic Orders and Kidney Infection Regression Model [PDF]
Journal of Sciences, Islamic Republic of Iran, 2021 We introduce a method to generate a new class of lifetime models based on the bounded distributions such that the defined models are exclusively a special case of the new class.
Araf Khanjari Idenak +2 more
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Stochastically ordered multiple regression [PDF]
Biostatistics, 2010 In various application areas, prior information is available about the direction of the effects of multiple predictors on the conditional response distribution. For example, in epidemiology studies of potentially adverse exposures and continuous health responses, one can typically assume a priori that increasing the level of an exposure does not lead ...
Bornkamp, Björn +2 more
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Periodic Fluctuations in the Incidence of Gastrointestinal Cancer
Frontiers in Oncology, 2021 PurposeNative stem cells can be periodically replaced during short and long epigenetic intervals. Cancer-prone new stem cells might bring about periodic (non-stochastic) carcinogenic events rather than stochastic events.
Mun-Gan Rhyu +5 more
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Regression and progression in stochastic domains [PDF]
Artificial Intelligence, 2020 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Belle, Vaishak, Levesque, Hector J.
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