Results 1 to 10 of about 1,669,248 (311)

On Nonparametric Estimation of Covariogram

Austrian Journal of Statistics
The paper overviews and investigates several nonparametric methods of estimating covariograms. It provides a unified approach and notation to compare the main approaches used in applied research.
Adam Bilchouris, Andriy Olenko
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On nonparametric spectral estimation [PDF]

Circuits Systems and Signal Processing, 1999
Publication in the conference proceedings of EUSIPCO, Rhodes, Greece ...
Tomas Sundin, Petre Stoica
openaire   +2 more sources

Nonparametric Estimation [PDF]

, 2011
info:eu-repo/semantics ...
Jansen, Maarten, Claeskens, G.
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Nonparametric numerical approaches to probability weighting function construct for manifestation and prediction of risk preferences

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, Zhen-Song Chen, Witold Pedrycz, Kannan Govindan, Kwai-Sang Chin   +4 more
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Nonparametric Score Estimators

CoRR, 2020
Estimating the score, i.e., the gradient of log density function, from a set of samples generated by an unknown distribution is a fundamental task in inference and learning of probabilistic models that involve flexible yet intractable densities. Kernel estimators based on Stein's methods or score matching have shown promise, however their theoretical ...
Yuhao Zhou, Jiaxin Shi, Jun Zhu 0001
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The Curve Estimation of Combined Truncated Spline and Fourier Series Estimators for Multiresponse Nonparametric Regression

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, I Nyoman Budiantara, Ismaini Zain   +2 more
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NONPARAMETRIC ESTIMATION WITH AGGREGATED DATA [PDF]

Econometric Theory, 2002
We introduce a kernel-based estimator of the density function and regression function for data that have been grouped into family totals. We allow for a common intrafamily component but require that observations from different families be independent. We establish consistency and asymptotic normality for our procedures.
Oliver Linton, Yoon-Jae Whang
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All models are wrong, but which are useful? Comparing parametric and nonparametric estimation of causal effects in finite samples

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., Williams Nicholas T., Miles Caleb H., Antonelli Joseph, Diaz Ivan   +4 more
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NONPARAMETRIC ESTIMATION OF HOMOGENEOUS FUNCTIONS [PDF]

Econometric Theory, 2003
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Tripathi, Gautam, Kim, Woocheol
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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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