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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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Inferring structure and parameters of stochastic reaction networks with logistic regression. [PDF]
PLoS ONEIdentifying network structure and estimating reaction parameters remain central challenges in modeling chemical reaction networks. In this work, we develop likelihood-based methods that use multinomial logistic regression to infer both stoichiometries ...
Boseung Choi +2 more
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A regression-based Monte Carlo method to solve backward stochastic differential equations
Annals of Applied Probability, 2005 We are concerned with the numerical resolution of backward stochastic differential equations. We propose a new numerical scheme based on iterative regressions on function bases, which coefficients are evaluated using Monte Carlo simulations.
Emmanuel Gobet, Xavier Warin
exaly +4 more sources
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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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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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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Generalized Stochastic Restricted LARS Algorithm
Ruhuna Journal of Science, 2022 The Least Absolute Shrinkage and Selection Operator (LASSO) is used to tackle both the multicollinearity issue and the variable selection concurrently in the linear regression model.
Manickavasagar Kayanan +1 more
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Modeling and Calibration for Some Stochastic Differential Models
Fractal and Fractional, 2022 In many scientific fields, the dynamics of the system are often known, and the main challenge is to estimate the parameters that model the behavior of the system.
Abdelmalik Moujahid, Fernando Vadillo
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Entropy-Randomized Forecasting of Stochastic Dynamic Regression Models
Mathematics, 2020 We propose a new forecasting procedure that includes randomized hierarchical dynamic regression models with random parameters, measurement noises and random input.
Yuri S. Popkov +3 more
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