Mediaspace scheduled maintenance: Aug 25, 2026 07:00 - 12:00 AM. During this time, videos will be temporarily unavailable. Check status updates.

Concept

Non-linear least squares

Related lectures (30)

Linear Regression Testing

Explores least squares in linear regression, hypothesis testing, outliers, and model assumptions.

Regression II

Delves into regression analysis, emphasizing distributional checks, weighted least squares, and hypothesis testing.

Recursive Least-Squares: Weighted Formulation

Covers the Recursive Least-Squares algorithm with weighted formulation for real-time data updating.

Multilinear Regression: Least Square Fit

Covers multilinear regression using least square fit method and the importance of standardizing variables.

Plackett-Burman Design: Hadamard Matrix

Explores the construction and application of Hadamard matrices for efficient estimation of main effects without interactions in the Plackett-Burman Design.

Statistical Inference for Bandit Data

Explores statistical inference for bandit data, focusing on personalized treatment actions and challenges of standard estimators.

Model Specification in Time Series

Covers the identification and model specification in time series analysis, including AR models and least squares estimation.

Linear Equations: Least Squares Solution MOOC: Linear Algebra (Part 3)

Explains how to solve linear equations using the least squares method to minimize errors in the system.

Newton's method: Hessian and optimization

Explores Newton's method for optimization, emphasizing the role of the Hessian matrix.

NonLinear Regression

Explores non-linear regression models, likelihood estimation, model fitting, and confidence intervals.

Multilinear Regression: Basics and Applications

Covers the basics of multilinear regression and its application in analyzing material properties.

Hadamard Design: Introduction and Construction

Introduces Hadamard and Plackett-Burman designs, explaining construction, analysis, and optimization techniques.

Approximation of Data

Covers the least squares method for approximating data and handling errors.

Splines: Fundamentals and Applications

Explores B-splines, natural cubic splines, and smoothing splines in regression problems and their practical applications.

Geometry and Least Squares

Discusses the geometry of least squares, exploring row and column perspectives, hyperplanes, projections, residuals, and unique vectors.

Linear Algebra in Data Science

Explores the application of linear algebra in data science, covering variance reduction, model distribution theory, and maximum likelihood estimates.

Interpolation: Applications and Techniques

Explores interpolation applications in biological tissue and population census data analysis using the method of least squares.

Subspace-based approximations

Explores subspaces, approximation problems, and least-squares approximation methods.

Splines: Least-Squares Method Log in to Mediaspace to watch this video

Explores splines, emphasizing the least-squares method for interpolating splines and demonstrating its application using MATLAB.

Modeling Response Surfaces in Matlab Log in to Mediaspace to watch this video

Covers modeling response surfaces in Matlab, including building the model, defining the domain, computing values, and analyzing residuals.