Method of moments (electromagnetics)

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Related lectures (13)

Statistical Estimation: Maximum Likelihood

Explores Maximum Likelihood Estimation properties, challenges, and alternative methods in statistical inference.

Estimation and Method of Moments

Covers the definition of statistics and estimators, examples of estimators, and the method of moments.

Generalized Method of Moments (GMM)

Introduces the Generalized Method of Moments (GMM), a versatile approach for estimation based on moment restrictions, with applications in asset pricing models.

Maximum Likelihood Theory & Applications

Covers maximum likelihood theory, applications, and hypothesis testing principles in econometrics.

Point Estimation Methods: MOM and MLE

Explores point estimation methods like MOM and MLE, discussing bias, variance, and examples.

Estimation Methods: Point Estimate and Maximum Likelihood

Discusses different estimators and how to choose between them, emphasizing calculation and properties.

Estimating R: Maximum Likelihood Method

Explores estimating parameters in statistical models using the maximum likelihood method and the method of moments.

Confidence Intervals: Definition and Estimation

Explains confidence intervals, parameter estimation methods, and the central limit theorem in statistical inference.

Estimation: Point Estimators

Covers point estimators for statistical parameter estimation, including methods and calculations.

Implicit Generative Models

Explores implicit generative models, covering topics like method of moments, kernel choice, and robustness of estimators.

Statistics for Data Science: Introduction to Statistical Methods

Covers the fundamental concepts of statistics and their application in data science.

Statistical Estimation

Covers statistical estimation methods and explores practical examples of parameter estimation for different distributions.

Basic Principles of Point Estimation

Explores the Method of Moments, Bias-Variance tradeoff, Consistency, Plug-In Principle, and Likelihood Principle in point estimation.

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