Estimating the error variance in matrix form - part 1 @SpartacanUsuals
Estimating the error variance in matrix form - part 1  @SpartacanUsuals
Uploaded November 2013 | Updated September 2026, 1 hour ago
In this video the explicit form of an unbiased estimator of the error variance is derived.

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 1Bayesian posterior samplingAn introduction to Gibbs samplingMaximum Likelihood: Bernoulli random variables estimator variance part 2An introduction to importance sampling - optimal importance distributionsAn introduction to continuous marginal probability distributionsHow to check if treatment is randomly assigned?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 matching
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Estimating the error variance in matrix form - part 1

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