Maximum likelihood: Normal error distribution - estimator variance part 1 @SpartacanUsuals
Maximum likelihood: Normal error distribution - estimator variance part 1  @SpartacanUsuals
Uploaded October 2013 | Updated September 2026, 59 minutes ago
This video works through for the estimated asymptotic variance of Maximum Likelihood estimators of the mean and variance, in a standard normally distributed population error model.

Check out oxbridge-tutor.co.uk/undergraduate-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
Maximum 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 convergenceHow to use rejection sampling to uniformly sample within a cows boundariesMaximum likelihood: Normal error distribution - estimator variance part 3Why is a likelihood not a probability distribution?The variance of GLS estimatorsExample likelihood model: waiting times between beer ordersBLUE estimators in presence of heteroscedasticity - GLS - part 2An introduction to the Beta distributionMaximum Likelihood: Bernoulli random variables estimator variance part 1
Ben Lambert |

Maximum likelihood: Normal error distribution - estimator variance part 1

SHARE TO X SHARE TO REDDIT SHARE TO FACEBOOK WALLPAPER