Results 1 to 10 of about 229,123 (176)
Technological and Economic Development of Economy, 2023 Probability weighting function (PWF) is the psychological probability of a decision-maker for objective probability, which reflects and predicts the risk preferences of decision-maker in behavioral decisionmaking.
Sheng Wu +4 more
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Mathematics, 2021 Nonparametric regression becomes a potential solution if the parametric regression assumption is too restrictive while the regression curve is assumed to be known.
Helida Nurcahayani +2 more
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Nonparametric Pointwise Estimation for a Regression Model with Multiplicative Noise
Journal of Function Spaces, 2021 In this paper, we consider a general nonparametric regression estimation model with the feature of having multiplicative noise. We propose a linear estimator and nonlinear estimator by wavelet method.
Jia Chen, Junke Kou
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Asymptotics for L 1 $L_{1}$ -wavelet method for nonparametric regression
Journal of Inequalities and Applications, 2020 Wavelets are particularly useful because of their natural adaptive ability to characterize data with intrinsically local properties. When the data contain outliers or come from a population with a heavy-tailed distribution, L 1 $L_{1}$ -estimation should
Xingcai Zhou, Fangxia Zhu
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Journal of Causal Inference, 2023 There is a long-standing debate in the statistical, epidemiological, and econometric fields as to whether nonparametric estimation that uses machine learning in model fitting confers any meaningful advantage over simpler, parametric approaches in finite ...
Rudolph Kara E. +4 more
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Nonparametric Mean Estimation for Big-but-Biased Data
Proceedings, 2018 Some authors have recently warned about the risks of the sentence with enough data, the numbers speak for themselves. The problem of nonparametric statistical inference in big data under the presence of sampling bias is considered in this work.
Laura Borrajo, Ricardo Cao
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Media Statistika, 2008 If X is predictor variable and Y is response variable of following model Y = f (X) +e with function f is regression which not yet been known and e is independent random variable with mean 0 and variant , hence function of f can estimate with parametric ...
Suparti Suparti +2 more
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High throughput nonparametric probability density estimation. [PDF]
PLoS ONE, 2018 In high throughput applications, such as those found in bioinformatics and finance, it is important to determine accurate probability distribution functions despite only minimal information about data characteristics, and without using human subjectivity.
Jenny Farmer, Donald Jacobs
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Mathematics, 2023 For nonparametric regression estimation, conventional research all focus on isotropic regression function. In this paper, a linear wavelet estimator of anisotropic regression function is constructed, the rate of convergence of this estimator is discussed
Jia Chen, Junke Kou
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Characterization of the asymptotic distribution of semiparametric M-estimators [PDF]
, 2010 This paper develops a concrete formula for the asymptotic distribution of two-step, possibly non-smooth semiparametric M-estimators under general misspecification.
Ichimura, H, Lee, S
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