Fractal Perturbation of the Nadaraya–Watson Estimator
Fractal and Fractional, 2022 One of the main tasks in the problems of machine learning and curve fitting is to develop suitable models for given data sets. It requires to generate a function to approximate the data arising from some unknown function.
Dah-Chin Luor, Chiao-Wen Liu
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Application of the Nadaraya-Watson estimator based attention mechanism to the field of predictive maintenance [PDF]
MethodsXAttention mechanism has recently gained immense importance in the natural language processing (NLP) world. This technique highlights parts of the input text that the NLP task (such as translation) must pay “attention” to.
Rajesh Siraskar +4 more
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Heterogeneous Treatment Effect with Trained Kernels of the Nadaraya–Watson Regression
Algorithms, 2023 A new method for estimating the conditional average treatment effect is proposed in this paper. It is called TNW-CATE (the Trainable Nadaraya–Watson regression for CATE) and based on the assumption that the number of controls is rather large and the ...
Andrei V Konstantinov +2 more
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Nonparametric Expectile Shortfall Regression for Complex Functional Structure [PDF]
EntropyThis paper treats the problem of risk management through a new conditional expected shortfall function. The new risk metric is defined by the expectile as the shortfall threshold.
Mohammed B. Alamari +3 more
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Application of non-parametric models for analyzing survival data of COVID-19 patients [PDF]
Journal of Infection and Public Health, 2021 Background: COVID-19 Coronavirus variants are emerging across the globe causing ongoing pandemics. It is important to estimate the case fatality ratio (CFR) during such an epidemic of a potentially fatal disease. Methods: Firstly, we have performed a non-
Sarada Ghosh +2 more
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Inference About Separable Causal Effects With Longitudinal Bivariate Ordinal Responses With Missingness and Censoring. [PDF]
Stat MedABSTRACT Causal inference has gained extensive attention in various fields, including healthcare, epidemiology, and social sciences. While many methods have been developed, most research has been directed to handle data with a univariate response variable.
Hu P, Yi GY.
europepmc +2 more sources
Barekeng, 2022 ISSI reflects the movement of sharia stock prices as a whole. It is necessary to forecast the share price to help investors determine whether the shares should be sold, bought, or retained. This study aims to predict the value of ISSI using nonparametric
Yuniar Farida +2 more
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Local Linear Regression Estimator on the Boundary Correction in Nonparametric Regression Estimation
Journal of Statistical Theory and Applications (JSTA), 2020 The precision and accuracy of any estimation can inform one whether to use or not to use the estimated values. It is the crux of the matter to many if not all statisticians.
Langat Reuben Cheruiyot
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Smoothing parameter selection in Nadaraya-Watson kernel nonparametric regression using nature-inspired algorithm optimization [PDF]
المجلة العراقية للعلوم الاحصائية, 2020 In the context of Nadaraya-Watson kernel nonparametric regression, the curve estimation is fully depending on the smoothing parameter. At this point, the nature-inspired algorithms can be used as an alternative tool to find the optimal selection. In this
Zinah Basheer, Zakariya Algamal
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Mathematics, 2023 This paper studies the estimation problem for semi-varying coefficient heteroscedastic instrumental variable models with missing responses. First, we propose the adjusted estimators for unknown parameters and smooth functional coefficients utilizing the ...
Weiwei Zhang, Jingxuan Luo, Shengyun Ma
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