Results 31 to 40 of about 117,399 (299)
A-Spline Regression for Fitting a Nonparametric Regression Function with Censored Data
Stats, 2020 This paper aims to solve the problem of fitting a nonparametric regression function with right-censored data. In general, issues of censorship in the response variable are solved by synthetic data transformation based on the Kaplan–Meier estimator in the
Ersin Yılmaz +2 more
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qgam: Bayesian Nonparametric Quantile Regression Modeling in R
Journal of Statistical Software, 2021 Generalized additive models (GAMs) are flexible non-linear regression models, which can be fitted efficiently using the approximate Bayesian methods provided by the mgcv R package.
Matteo Fasiolo +4 more
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Nonparametric LAD cointegrating regression [PDF]
Journal of Multivariate Analysis, 2013 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Barekeng, 2023 This study used a biresponse nonparametric regression method with truncated spline estimation that used two response variables. Nonparametric regression method is used when the regression curve is not known for its shape and pattern.One of the ...
Ar Ruum Mia Sari +2 more
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Nonparametric estimation of an additive quantile regression model [PDF]
, 2004 This paper is concerned with estimating the additive components of a nonparametric additive quantile regression model. We develop an estimator that is asymptotically normally distributed with a rate of convergence in probability of n^{-r/(2+10)} when ...
Joel L. Horowitz +5 more
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Nonparametric Bayesian Regression
The Annals of Statistics, 1986 The paper addresses itself to Bayesian estimation of the function \[ F(x_ 1,x_ 2)=m+a(x_ 1)+b(x_ 2)+c(x_ 1,x_ 2) \] in the model \(y_ i=F(x_{1i},x_{2i})+e_ i\). A prior for F is constructed by putting independent priors on m,a,b, and c. They are normal distribution and Brownian motion.
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Fourier Series Nonparametric Regression Modeling in the Case of Rainfall in West Java Province
IJID (International Journal on Informatics for Development), 2022 The Fourier series is a trigonometric polynomial that has flexibility, so it adapts effectively to the local nature of the data. This Fourier series estimator is generally used when the data used is investigated for unknown patterns and there is a ...
Anatansyah Ayomi Anandari +2 more
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Development of nonparametric geographically weighted regression using truncated spline approach [PDF]
Songklanakarin Journal of Science and Technology (SJST), 2018 Nonparametric geographically weighted regression with truncated spline approach is a new method of statistical science. It is used to solve the problems of regression analysis of spatial data if the regression curve is unknown.
Sifriyani +3 more
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Barekeng, 2022 The nonparametric regression model is applied to regression curves for which the regression curve is unknown. Fourier series estimation is an approach in nonparametric regression, which has high flexibility and is able to adjust to the local nature of ...
Muhammad Danil Pasarella +2 more
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Molecular Oncology, EarlyView.Intratumour heterogeneity complicates precision management of advanced endometrial cancer. Circulating tumor DNA (ctDNA) offers a minimally invasive strategy to capture tumor evolution and therapeutic resistance. Here, we compare tumor‐agnostic NGS with tumor‐informed ddPCR, outlining their relative sensitivity, concordance, and clinical implications ...
Carlos Casas‐Arozamena +15 more
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