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Related lectures (32)

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Regression: Linear Models

Introduces linear regression, generalized linear models, and mixed-effect models for regression analysis.

Modern Regression: Spring Barley Data

Covers inference, weighted least squares, spring barley data analysis, and smoothing techniques.

Optimal Control: Equivalent Problems

Discusses optimal control with a focus on three equivalent problems related to elastic strings.

Generalized Additive Models: Penalized Iterative Weighted Least Squares

Covers the introduction to generalized additive models and iterative weighted least squares for model checking and smooth fits.

Regression Methods: Model Building and Inference

Covers Inference, Model Building, Variable Selection, Robustness, Regularised Regression, Mixed Models, and Regression Methods.

Inference and Mixed Models

Covers point estimation, confidence intervals, and hypothesis testing for smooth functions using mixed models and spline smoothing.

Generalized Additive Models: Applications and Techniques

Explores Generalized Additive Models, covering basics, smooth functions, penalties, practical examples in R, and linear mixed models.

Natural Cubic Splines

Explains the construction of natural cubic splines, emphasizing smoothness and continuity in the function representation.

Generalized Linear Models: Exponential Families and Model Construction

Covers exponential families, model construction, and canonical link functions in Generalized Linear Models.

CMOS Circuits: Metabolites Detection

Explores CMOS circuits for metabolites detection in fixed-voltage cells, covering operational amplifier features, saturation risks, temperature compensation, and current measurement techniques.