Estimating the error variance in matrix form - part 6 @SpartacanUsuals
Estimating the error variance in matrix form - part 6  @SpartacanUsuals
Uploaded November 2013 | Updated September 2026, 1 hour ago
This video explains the concept of the Orthogonal Projection Operator in Ordinary Least Squares estimation, and derives its explicit matrix form.

Check out oxbridge-tutor.co.uk/graduate-econometrics-course for course materials, and information regarding updates on each of the courses. Check out ben-lambert.com/econometrics-course-problem-sets-and-data for course materials, and information regarding updates on each of the courses. Quite excitingly (for me at least), I am about to publish a whole series of new videos on Bayesian statistics on youtube. See here for information: ben-lambert.com/bayesian Accompanying this series, there will be a book: amazon.co.uk/gp/product/1473916364/ref=pe_3140701_247401851_em_1p_0_ti
Estimating the error variance in matrix form - part 6Variance-covariance matrix using matrix notation of factor analysisIntroduction to the matrix formulation of econometricsAn introduction to Jeffreys priors - 3Sample balancing via stratification and matchingModel implied variance-covariance matrix of indicators (matrix form) - part 1An introduction to the Poisson distribution - 1Effective sample size: representing the cost of dependent samplingMaximum likelihood: Normal error distribution - estimator variance part 1Simultaneous equation models - an introductionAn introduction to numerical integration through Gaussian quadratureBob’s bees: the importance of using multiple bees (chains) to judge MCMC convergence
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Estimating the error variance in matrix form - part 6

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