Related lectures (32)
Long Memory and ARCH: Time Series Math 342
Explores long memory in time series and Autoregressive Conditional Heteroskedasticity processes in financial data.
Hadamard Design: Introduction and Construction
Introduces Hadamard and Plackett-Burman designs, explaining construction, analysis, and optimization techniques.
Dependence and Correlation
Explores dependence, correlation, and conditional expectations in probability and statistics, highlighting their significance and limitations.
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.
Statistics essentials: ANOVA
Covers the essentials of ANOVA, explaining its concept, calculations, assumptions, and interpretation of results.
Long Memory and ARCH: Time Series
Explores long memory in time series and ARCH models for financial volatility.
Conditional Density and Expectation
Explores conditional density, expectations, and independence of random variables with practical examples.
Multivariable Control
Covers Gaussian random variables, affine transformations, and linear systems driven by Gaussian noise in multivariable control.
Stratified Sampling: Theory and Applications
Explores stratified sampling, dividing a population into subgroups for more accurate sampling.
ARCH and GARCH Models
Explores ARCH and GARCH models, volatility clustering, time series, estimation, and filtering steps in financial and macroeconomic contexts.

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