NonLinear Regression

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Related lectures (50)

Linear Regression Basics Log in to Mediaspace to watch this video

Covers the basics of linear regression, instrumental variables, heteroskedasticity, autocorrelation, and Maximum Likelihood Estimation.

Basics of linear regression model Log in to Mediaspace to watch this video

Covers the basics of linear regression, OLS method, predicted values, residuals, matrix notation, goodness-of-fit, hypothesis testing, and confidence intervals.

Regression: Simple and Multiple Linear Log in to Mediaspace to watch this video

Covers simple and multiple linear regression, including least squares estimation and model diagnostics.

Linear Regression: Basics and Applications Log in to Mediaspace to watch this video

Explores linear regression using the method of least squares to fit data points with the equation y = ax + b.

Linear Regression: Regularization Log in to Mediaspace to watch this video

Covers linear regression, regularization, and probabilistic models in generating labels.

Linear Regression: Beyond the Basics Log in to Mediaspace to watch this video

Explores advanced concepts in linear regression models, including multicollinearity, hypothesis testing, and handling outliers.

Linear Regression: Estimation and Prediction Log in to Mediaspace to watch this video

Covers the basics of linear regression, focusing on estimation and prediction.

Linear Regression: Fundamentals and Applications Log in to Mediaspace to watch this video

Explores linear regression fundamentals, model training, evaluation, and performance metrics, emphasizing the importance of R², MSE, and MAE.

Linear and Weighted Regression: Optimal Parameters and Local Solutions Log in to Mediaspace to watch this video

Covers linear and weighted regression, optimal parameters, local solutions, SVR application, and regression techniques' sensitivity.

Logistic Regression: Classification Log in to Mediaspace to watch this video

Covers supervised learning, classification using logistic regression, and challenges in optimization.

Linear Regression: Foundations and Applications Log in to Mediaspace to watch this video

Introduces linear regression, covering its fundamentals, applications, and evaluation metrics in machine learning.

Calibration Curves in Quantitative Ligand Binding Assays Log in to Mediaspace to watch this video

Covers the importance of calibration curves in ensuring accurate sample quantitation in ligand binding assays.

Likelihood Inference Log in to Mediaspace to watch this video

Covers iterative weighted least squares, Poisson regression, mixed models, and likelihood ratio statistic.

Linear Models for Classification: Logistic Regression and SVM Log in to Mediaspace to watch this video

Covers linear models for classification, focusing on logistic regression and support vector machines.

Estimation and Confidence Intervals Log in to Mediaspace to watch this video

Explores parameter estimation, standard errors, and confidence intervals using the central limit theorem and practical examples.

Maximum Likelihood Estimation: Econometrics Log in to Mediaspace to watch this video

Introduces Maximum Likelihood Estimation in econometrics, covering principles, properties, applications, and specification tests.

Regularization Techniques Log in to Mediaspace to watch this video

Explores regularization in linear models, including Ridge Regression and the Lasso, analytical solutions, and polynomial ridge regression.

Interval Estimation Log in to Mediaspace to watch this video

Covers the construction of confidence intervals for a normal distribution with unknown mean and variance.

Stochastic Simulation: Monte Carlo Method Log in to Mediaspace to watch this video

Covers the properties and error estimates of the Monte Carlo method in stochastic simulation.

Surfaces in Geometry II Log in to Mediaspace to watch this video

Explores geometric surfaces, rules between shapes, and architectural applications.

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