Spline Estimator in Multi-Response Nonparametric Regression Model
Jurnal Ilmu Dasar, 2010 In many applications two or more dependent variables are observed at several values of the independent variables, such as at time points. The statistical problems are to estimate functions that model their dependences on the independent variables, and to
Budi Lestari +3 more
doaj
BarekengNonparametric regression is a regression approach that is used to determine the relationship between the response variable and the predictor variable if the shape of the regression curve is unknown.
Rahmania Rahmania +2 more
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Data‐Guided Photocatalysis: Supervised Machine Learning in Water Splitting and CO2 Conversion
Advanced Intelligent Discovery, EarlyView.This review highlights recent advances in supervised machine learning (ML) for photocatalysis, emphasizing methods to optimize photocatalyst properties and design materials for solar‐driven water splitting and CO2 reduction. Key applications, challenges, and future directions are discussed, offering a practical framework for integrating ML into the ...
Paul Rossener Regonia +1 more
wiley +1 more source
A SIEVE STOCHASTIC GRADIENT DESCENT ESTIMATOR FOR ONLINE NONPARAMETRIC REGRESSION IN SOBOLEV ELLIPSOIDS. [PDF]
Ann Stat, 2022 Zhang T, Simon N.
europepmc +1 more source
Rodeo: Sparse Nonparametric Regression in High Dimensions
, 2005 We present a greedy method for simultaneously performing local bandwidth selection and variable selection in nonparametric regression. The method starts with a local linear estimator with large bandwidths, and incrementally decreases the bandwidth of ...
Lafferty, John, Wasserman, Larry
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AS‐pHopt: An Optimal pH Prediction Model Enhanced by Active Site of Enzymes
Advanced Intelligent Discovery, EarlyView.To address the low accuracy of enzyme optimal pH (pHopt) prediction, this study develops active site‐based pHopt (AS‐pHopt), a prediction model enhanced by active site information and pseudo‐label prediction. Integrating key structural and physicochemical features affecting enzyme pHopt, AS‐pHopt uses Evolutionary Scale Modeling (ESM)‐2 with active ...
Wenxiang Song +6 more
wiley +1 more source
A Note on Parametric and Nonparametric Regression in the Presence of Endogenous Control Variables [PDF]
This note argues that nonparametric regression not only relaxes functional form assumptions vis-a-vis parametric regression, but that it also permits endogenous control variables.
Markus Frölich
core
On the Nonparametric Estimation of Regression Functions
Journal of the Royal Statistical Society Series B: Statistical Methodology, 1977 Summary We consider a nonparametric technique proposed by Priestley and Chao (1972) for estimating an unknown regression function. Conditions for strong convergence and asymptotic normality are discussed. Special consideration is given to the optimal choice of a weighting function.
openaire +2 more sources
Adaptive Macroscopic Ensemble Allocation for Robot Teams Monitoring Spatiotemporal Processes
Advanced Intelligent Systems, EarlyView.We propose an online, environment feedback‐driven macroscopic ensemble approach to adapt robot team task allocation in spatiotemporal environments by controlling robot populations rather than assigning individual robots, all while maintaining robust team performance even for small teams. Our simulation and experimental results show better or comparable
Victoria Edwards +2 more
wiley +1 more source
Determination of the best knot and bandwidth in geographically weighted truncated spline nonparametric regression using generalized cross validation. [PDF]
MethodsX, 2023 Putra R, Fadhlurrahman MG, Gunardi.
europepmc +1 more source