Copulas and Extreme Values

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Related lectures (29)

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Estimating R: Marginal and Conditional Distributions

Covers the estimation of R using bivariate normal distributions and explores the marginal and conditional distributions of X₁ and X₂.

Distribution Theory of Least Squares

Explores the distribution theory of least squares estimators in a Gaussian linear model.

Linear Combinations: Moment-Generating Functions

Explores moment-generating functions, linear combinations, and normality of random variables.

Normal Distribution: Properties and Calculations

Covers properties and calculations related to the normal distribution, including probabilities and quantiles.

Probability Distributions

Covers various probability distributions and their applications in real-world scenarios.

Statistical Analysis: Boxplot and Normal Distribution

Introduces statistical analysis concepts like boxplot and normal distribution using real data examples.

Normal Distribution: Characteristics and Z-scores

Explores normal distribution characteristics, Z-scores, probability in inferential statistics, sample effects, and binomial distribution approximation.

Probabilities and Statistics

Covers fundamental concepts in probabilities and statistics, including linear regression, exploratory statistics, and the analysis of probabilities.

Describing Data: Statistics and Hypothesis Testing

Covers descriptive statistics, hypothesis testing, and correlation analysis with various probability distributions and robust statistics.