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Mattias Villani
Professor of Statistics at Stockholm University
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Bayesian Learning
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Fork of Hypothesis test for a mean in a normal population
Bayesian Learning
Bernoulli distributionMaximum likelihood - Bernoulli dataBayes' theorem for eventsBayesian inference for Bernoulli iid dataBayesian inference for Gaussian iid data with known varianceMaximum likelihood for iid Poisson dataBayesian inference for iid Poisson countsBayesian inference for Exponential iid dataBayesian credible intervalsScaled inverse chi2 distributionBayesian inference for Gaussian iid dataBayesian inference for multinomial dataAutoregressive processes - simulation and priorsPrior predictive - iid Poisson model with Gamma priorMultivariate normal distributionBayesian linear regressionCentral limit theoremLaw of Large NumbersThe Taylor approximationSecond derivative measures the curvature of a functionRandom Walk MetropolisHamiltonian Markov Chain Monte CarloLeapfrog IntegratorHMC sampling from multi-modal distributionsPosterior approximation - Beta model for proportionsDirichlet DistributionDistributions on the unit simplexMaximum likelihood - Poisson regressionKullback-Leibler divergence - continuous distributionsConfidence interval for a proportionCoverage of interval estimates for a proportionApproximating the Binomial distributionSampling distribution and likelihood function - Normal modelSampling distribution and likelihood function - Bernoulli model
Bayesian hypothesis test for a mean in a normal population
Distribution of the maximum - a tale of tails
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Platform
  • Observable Canvases
  • Observable Notebooks
  • Pricing
Docs
  • Observable
  • Observable Framework
  • Observable Plot
  • D3
  • Release notes
Resources
  • Blog
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  • Customer stories
  • Community Slack
  • Forum
Company
  • About
  • Careers
  • GitHub
GitHubLinkedInBlueskyYouTubeX
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