Results 11 to 20 of about 12,193,766 (206)
Non‐parametric regression for networks [PDF]
Stat, 2021 Network data are becoming increasingly available, and so there is a need to develop a suitable methodology for statistical analysis. Networks can be represented as graph Laplacian matrices, which are a type of manifold‐valued data. Our main objective is to estimate a regression curve from a sample of graph Laplacian matrices conditional on a set of ...
Katie E. Severn +2 more
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Imitation learning with non-parametric regression [PDF]
Proceedings of 2012 IEEE International Conference on Automation, Quality and Testing, Robotics, 2012 Humans are very fast learners. Yet, we rarely learn a task completely from scratch. Instead, we usually start with a rough approximation of the desired behavior and take the learning from there. In this paper, we use imitation to quickly generate a rough solution to a robotic task from demonstrations, supplied as a collection of state-space ...
Vaandrager, Maarten +3 more
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Comparison of Parametric and Nonparametric Forecasting Methods for Daily COVID-19 Cases in Malaysia
JOIV: International Journal on Informatics Visualization, 2023 Numerous research studies are currently examining various measures to control the transmission of COVID-19. One essential task in this regard is predicting or forecasting the number of infected individuals.
I Made Artha Agastya, Afrig Aminuddin
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Remote Sensing, 2023 Altimeter data processing is very important to improve the quality of sea surface height (SSH) measurements. Sea state bias (SSB) correction is a relatively uncertain error correction due to the lack of a clear theoretical model. At present, the commonly
Jinyun Guo +4 more
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EJNMMI Physics, 2023 Full quantification of Positron Emission Tomography (PET) requires an arterial input function (AIF) for measurement of certain targets, or using particular radiotracers, or for the quantification of specific outcome measures.
Granville J. Matheson +7 more
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Journal of Modern Power Systems and Clean Energy, 2022 Accurate transient stability assessment (TSA) and effective preventive control are important for the stable operation of power systems. With the superiorities in precision and efficiency, data-driven methods are widely used in TSA nowadays.
Yiwei Fu +5 more
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A Novel EM-Type Algorithm to Estimate Semi-Parametric Mixtures of Partially Linear Models
Mathematics, 2023 Semi- and non-parametric mixture of normal regression models are a flexible class of mixture of regression models. These models assume that the component mixing proportions, regression functions and/or variances are non-parametric functions of the ...
Sphiwe B. Skhosana +2 more
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M-quantile regression analysis of temporal gene expression data [PDF]
, 2009 In this paper, we explore the use of M-regression and M-quantile coefficients to detect statistical differences between temporal curves that belong to different experimental conditions.
Vinciotti, V +3 more
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Non-parametric regression for robot learning on manifolds
CoRR, 2023 17 pages, 15 figures; added quantitative comparisons with baselines in the experiments Section; modified introduction; fixed typos; added Appendixes B and C; reordered sections for better understanding; changed the Section on adaptation of ...
Pablo C. López-Custodio +3 more
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Non-parametric specification testing of non-nested econometric models [PDF]
, 1994 We consider the non-nested testing prqblem of non-parametric regressions. We show that, when the regression functions are unknown under both the null and the alternative hypotheses, an extension of the J-test procedure of Davidson and Mackinnon (1981 ...
Delgado, Miguel A. +2 more
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