搜索资源列表
LIBRA_19jun09
- Our toolbox currently contains implementations of robust methods for location and scale estimation, covariance estimation (FAST-MCD), regression (FAST- LTS, MCD-regression), principal component analysis (RAPCA, ROBPCA), princi- pal component re
TimeSeriesPredictionUsingSupportVectorRegressionNe
- 为了选择神经网络的最好结构以及增强模型的推广能力，提出一种自适应支持向量回归神经网络(SVR—NN)。SVR—NN 用支持向量回归(SVR)方法获得网络的初始结构和权值， 白适应地生 成网络隐层结点，然后用基于退火过程的鲁棒学习算法更新网络结点疹教和权 主。 SVR—NN有很 好的收敛性和鲁棒性，能抑制由于数据异常和参数选择不当所导致的“过拟合，’现象。将SVR—NN 应用到时间序列预测上。结果表明，SVR．NN预测模型能精确地预测混沌时间序列，具有很好的 理论和应用价值。-Ab
TomCat
- Excellent code for robust regression and multivariate dataanalysis
TOMCAT
- 强健性多元回归工具箱，强健性PCA，强健性PLS-robust regression toolbox，including robust PCA，Robust PLS
K-Fold_CV_Tool
- MATLAB cross-validation tool for classification and regression v0.1 FEATURES: + K-fold cross validation. + Arbitrary train and prediction functions with parameters can be used. + Arbitrary loss function can be used. + Wrappers for
Fitting_with_MATLAB_1_
- 检查/剪裁的例子 孤立点检测实例 正交回归的例子 单因数变异数(泊松回归/逻辑回归)的例子 鲁棒回归的例子 特征选择的例子 常见的边坡问题的例子 -Censoring/clipping example Outlier detection example Orthogonal regression example GLM (Poisson regression/logistic regression) example Robust regress
matlab-econometric-toolbox
- “Applied Econometrics using MATLAB”配套的计量经济Matlab包-MATLAB code for: 1. least-squares, simultaneous systems (2SLS,3SLS, SUR) 2. limited dependent variable (logit, probit, tobit) and Bayesian variants 3. time-series (VAR, BVAR, ECM) estim
robustfit
- 稳健性回归分析拟合，带拟合阶数.属非线性最小二乘法，不受少量异常数据影响-Robust regression fitting with fitting order. Genus nonlinear least-squares method, a small amount of abnormal data is not affected
LSSVM
- 最小二乘支持向量机工具箱1.6版。含稳健回归和贝叶斯推理，功能强大。-LS-SVM Toolbox version 1.6. With robust regression and Bayesian inference, and powerful.
matlab-R2012a-Parametricstatistics
- matlab R2012a源代码（正太分解法计算均值和方差、图方法正太检验、M稳健回归）。-(calculated the mean and variance diagram method, inspection, teenage boy M robust regression teenage boy decomposition method). .
StatLSSVM
- 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 regre
LMS-program
- 稳健回归分析方法LMS，可以完成数据的LMS分析，具有很高的稳健性-the program for robust regression method LMS, which can be used directly.
SurfaceRoughness-master
- 计算表面粗糙度，可以选择高斯滤波、稳健高斯回归滤波，Ra、Rz、Rt(surface roughness Gaussian filtering and robust Gaussian regression filtering were selected)