Search - Nonparametric regression

Search - Nonparametric regression - List

[Other resource] K_smooth DL : 0: The subroutines glkern.f and lokern.f use an efficient and fast algorithm for automatically adaptive nonparametric regression estimation with a kernel method. Roughly speaking, the method performs a local averaging of the observations when estimating the regression function. Analogously, one can estimate derivatives of small order of the regression function.
Update : 2008-10-13 Size : 190.34kb Publisher : zhanglifang
[Algorithm] K_smooth DL : 0: The subroutines glkern.f and lokern.f use an efficient and fast algorithm for automatically adaptive nonparametric regression estimation with a kernel method. Roughly speaking, the method performs a local averaging of the observations when estimating the regression function. Analogously, one can estimate derivatives of small order of the regression function.
Update : 2025-04-04 Size : 190kb Publisher : zhanglifang
[Industry research] Eubank(1999)NonparametricRegressionandSplineSmoot DL : 0: Author:Eubank year:(1999)Name:Nonparametric Regression and Spline Smoothing second edition
Update : 2025-04-04 Size : 9.97mb Publisher : quinquindavid
[Other] heguji DL : 0: 非参数统计学中非参数回归的简单应用核回归程序，应用范围广泛，不需要知道样本的分布就可以使用该方法。-Non-parametric statistical regression Nonparametric kernel regression of the simple application procedure, a wide range of applications, does not need to know the distribution of the samples you can use this method.
Update : 2025-04-04 Size : 2kb Publisher : 林森
[Other] anrpdf DL : 0: 統計學範疇非線性回歸及smoothing的應用分析,高級教程-Applied Nonparametric Regression
Update : 2025-04-04 Size : 3.57mb Publisher : Andrea
[AI-NN-PR] duanshijianjiaotongliuyuce DL : 0: 数学建模中对交通流量短时间预测主要基于非参数估计回归-Mathematical Modeling of short-term traffic forecast is based on nonparametric regression estimation
Update : 2025-04-04 Size : 224kb Publisher : 杨阳
[Software Engineering] Eubank-R.-Nonparametric-Regression-and-Spline-Smo DL : 0: A introductory book about non-parametric statistics
Update : 2025-04-04 Size : 9.98mb Publisher : Allen
[Algorithm] Gaussian-Wavelet-Denoising- DL : 2: Gaussian的小波去噪工具箱，基于matlab-Gaussian Wavelet Denoising Matlab Toolbox Various wavelet shrinkage and wavelet thresholding estimators, appeared in the nonparametric regression literature, are implemented in MATLAB§. These estimators arise from a wide range of classical and empirical Bayes methods treating either individual or blocks of wavelet coefficients.
Update : 2025-04-04 Size : 288kb Publisher : hanyue
[Industry research] Kernel-Regression-for-Image-Processing DL : 0: In this paper, we make contact with the field of nonparametric statistics and present a development and generalization of tools and results for use in image processing and reconstruction. In particular, we adapt and expand kernel regression ideas for use in image denoising, upscaling, interpolation, fusion, and more. Furthermore, we establish key relationships with some popular existing methods and show how several of these algorithms, including the recently popularized bilateral filter, are special cases of the proposed framework. The resulting algorithms and analyses are amply illustrated with practical examples.
Update : 2025-04-04 Size : 8.89mb Publisher : ionutmirel
[Other] Prediction-of-frequency-response-after-generator. DL : 0: The ability of a regression tree method to properly interpolate among recorded data to give an estimate of the frequency decline following a generator outage is examined in this letter. The proposed method is a nonparametric technique that can select those system characteristics and their interactions that are most important in determining the relation between the generation/ load imbalance and the frequency decline. The information obtained from the proposed method can be used online for scheduling fast-acting reserve or load shedding for severe generator outage incidents
Update : 2025-04-04 Size : 152kb Publisher : jorgehas
[AI-NN-PR] StatLSSVM DL : 0: 支持向量机工具箱By Kris De Brabanter,标准的非参数回归，健壮的回归，一些调优标准等经典交叉验证，较好的交互性-The StatLSSVM toolbox is written so that only a few lines of code are necessary in order to perform standard nonparametric regression, regression with correlated errors and robust regression. In addition, construction of additive models and pointwise or uniform confidence intervals are also supported. A number of tuning criteria such as classical cross-validation, robust cross-validation and cross-validation for correlated errors are available. Also, minimization of the previous criteria is available without any user interaction.
Update : 2025-04-04 Size : 319kb Publisher : 李杰
[Other] curve_fitting_toolbox_curvefit_r2015a DL : 0: Curve Fitting Toolbox Product Description Fit curves and surfaces to data using regression, interpolation, and smoothing Curve Fitting Toolbox™ provides an app and functions for fitting curves and surfaces to data. The toolbox lets you perform exploratory data analysis, preprocess and post-process data, compare candidate models, and remove outliers. You can conduct regression analysis using the library of linear and nonlinear models provided or specify your own custom equations. The library provides optimized solver parameters and starting conditions to improve the quality of your fits. The toolbox also supports nonparametric modeling techniques, such as splines, interpolation, and smoothing. After creating a fit, you can apply a variety of post-processing methods for plotting, interpolation, and extrapolation estimating confidence intervals and calculating-Curve Fitting Toolbox Product Description Fit curves and surfaces to data using regression, interpolation, and smoothing Curve Fitting Toolbox™ provides an app and functions for fitting curves and surfaces to data. The toolbox lets you perform exploratory data analysis, preprocess and post-process data, compare candidate models, and remove outliers. You can conduct regression analysis using the library of linear and nonlinear models provided or specify your own custom equations. The library provides optimized solver parameters and starting conditions to improve the quality of your fits. The toolbox also supports nonparametric modeling techniques, such as splines, interpolation, and smoothing. After creating a fit, you can apply a variety of post-processing methods for plotting, interpolation, and extrapolation estimating confidence intervals and calculating
Update : 2025-04-04 Size : 10.13mb Publisher : maryam
[File Format] Wavelet-Shrinkage_-Asymptopia_ DL : 0: 小波变换阈值去噪的文章，基于最大最小准则计算-Minimax Estimation, Adaptive Estimation, Nonparametric Regression, Density Estimation, Spatial Adaptation, Wavelet Orthonormal bases, BesovSpaces, Optimal Recovery.
Update : 2025-04-04 Size : 270kb Publisher : 梁广柱
[matlab] 《MATLAB统计分析与应用2》 DL : 0: 一元方差分析；非参数方差分析；一元线性/非线性回归分析，多重回归分析(One way ANOVA, nonparametric ANOVA, single linear / nonlinear regression analysis, multiple regression analysis)
Update : 2025-04-04 Size : 160kb Publisher : ferryman
[Other] lwpfindh DL : 0: 局部加权多项式回归的目的是解决全球行为模型的表现不好或不能有效地应用于不必要的努力。LWP是一种非参数回归方法，是通过低阶多项式对数据子集进行逐点拟合局部。(Locally Weighted Polynomial regression is designed to address situations in which models of global behaviour do not perform well or cannot be effectively applied without undue effort. LWP is a nonparametric regression method that is carried out by pointwise fitting of low-degree polynomials to localized subsets of the data.)
Update : 2025-04-04 Size : 4kb Publisher : baidudu