Maximum likelihood estimation of factor analysis models - part 2 @SpartacanUsuals
Maximum likelihood estimation of factor analysis models - part 2  @SpartacanUsuals
Uploaded February 2014 | Updated September 2026, 2 hours ago
This video provides an introduction to maximum likelihood estimation of factor analysis (and sem) models, by minimising a fitting function which is intimately related to the log likelihood. 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
Maximum likelihood estimation of factor analysis models - part 2Why we typically use dependent sampling to sample from the posteriorAn introduction to the Poisson distribution - 2Score test (Lagrange Multiplier test) - introductionRepresenting heteroscedasticity in matrix formWhat is meant by overfitting?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 distributions
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Maximum likelihood estimation of factor analysis models - part 2

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