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Concept

Factor analysis

Related lectures (31)

Latent variables in choice models: Optima case study MOOC: Selected Topics on Discrete Choice

Explores the Optima case study, analyzing attitudes and mode choice.

Latent Factor Analysis: Movie Genre Classification

Explores latent factor analysis for movie genre classification based on male versus female leads.

Principal Component Analysis: Properties and Applications

Explores Principal Component Analysis theory, properties, applications, and hypothesis testing in multivariate statistics.

Quantitative Risk Management: Distributions and Techniques

Covers distributions and techniques in Quantitative Risk Management for financial modeling.

Multivariate Distributions: Spherical and Elliptical

Explores spherical and elliptical distributions, normal variance mixtures, factor models, and principal component analysis.

Functional Factor Models: Forecasting Mortality Curves in Japan

Explores high-dimensional functional factor models for forecasting mortality curves in Japan, discussing estimation, consistency, and application.

Understanding Preference Elicitation

Explores preference elicitation, latent variables, and the impact of external events on decision-making.

Structuring exploratory spatial data analysis

Explores the structured approach to exploratory spatial data analysis, emphasizing the importance of analytical frameworks and the Visual Seeking Mantra.

Principal Component Analysis: Dimensionality Reduction

Covers Principal Component Analysis for dimensionality reduction, exploring its applications, limitations, and importance of choosing the right components.

Multivariate Methods II: ICA for Functional Brain Imaging

Explores Independent Component Analysis in functional brain imaging, focusing on non-Gaussian sources, cleaning artefacts, and group studies.

Introduction: ESDA in environmental health

Introduces exploratory data analysis in environmental health, covering its definition, techniques, and applications in georeferenced health data analysis.

Causal Discovery: Latent Variable Models

Explores causal discovery using latent variable models, emphasizing the challenges and solutions in inferring causal relationships from non-Gaussian data.

Principal Components: Properties & Applications

Explores principal components, covariance, correlation, choice, and applications in data analysis.

Kernel PCA: Nonlinear Dimensionality Reduction

Explores Kernel Principal Component Analysis, a nonlinear method using kernels for linear problem solving and dimensionality reduction.

Knowledge Tracing: Student Learning and Latent Variables

Explores Bayesian Knowledge Tracing and latent variables for tracing student knowledge and making predictions.

Canonical Correlation Analysis: Linear and Kernel CCA

Introduces Canonical Correlation Analysis for finding joint features in separate datasets, extending to multimodal data and non-linear features.

Factor Models: Latent Variables and Asset Pricing Log in to Mediaspace to watch this video

Covers Factor Models, including PCA, asset pricing, factor investing, GMM, and Fama-McBeth estimation.

Wurzelkriterium: Majorantenkriterium Log in to Mediaspace to watch this video

Covers the Majorantenkriterium and Wurzelkriterium for convergence tests of series.

Statistical Analysis of Networks: Link Prediction and Biclustering Log in to Mediaspace to watch this video

Explores link prediction, logistic regression, causal inference, and biclustering in statistical network analysis.

Factor Models: Portfolio Optimization and APT Log in to Mediaspace to watch this video

Covers mean-variance portfolio choice, factor models, APT, Sharpe ratio, size and value anomalies, Fama and French models, and factor search.