Financial Data Analysis and Fitting
Analyzing and fitting financial data (stocks, futures, bonds) with computation of various technical indicators
Nonlinear Fitting and Data Prediction with Known Datasets Using MATLAB
Implement nonlinear fitting of known datasets and data prediction using MATLAB, with enhanced code implementation details
Interpolation and Fitting
MATLAB interpolation and fitting techniques (Linear fitting function: regress(), Polynomial curve fitting function: polyfit(), Polynomial evaluation function: polyval(), Polynomial fitting evaluation and confidence intervals function: polyconf(), Robust regression function: robustfit(), and custom function fitting capabilities)
A Comprehensive Hydrological Time Series Analysis Toolkit
A hydrological time series analysis toolkit featuring trend removal, curve fitting, periodic component extraction, and supporting algorithms for data preprocessing and model evaluation
Non-Uniform Rational B-Spline Curve Fitting
Develop a program for fitting non-uniform rational B-spline (NURBS) curves with robust data fitting capabilities
Chebyshev Polynomial Fitting for Satellite Precise Ephemerides
Chebyshev polynomial approximation of satellite precise ephemerides for orbital position and velocity determination, with implementation details and algorithm descriptions.
A Newly Proposed Machine Learning Algorithm for Classification and Regression: Relevance Vector Machine (RVM)
The Relevance Vector Machine (RVM) is a recently introduced machine learning method applicable to both classification and regression tasks. Compared to the well-established Support Vector Machine (SVM), RVM maintains excellent classification and regression performance while offering superior sparsity, resulting in enhanced generalization capabilities. This algorithm provides valuable insights for researchers in the machine learning field, with implementation advantages such as probabilistic outputs and automatic relevance determination through Bayesian inference.
Curve Fitting and Interpolation
Curve Fitting and Interpolation - Fundamental Techniques for Data Analysis and Prediction
Ellipsoidal Surface Fitting Using Least Squares Method
MATLAB Implementation: Fitting Ellipsoidal Surfaces with Least Squares Algorithm
Least Squares Surface Fitting Program (MATLAB Implementation)
MATLAB m-file implementation for least squares surface fitting of 3D data z=f(x,y) using polynomial approximation