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Hari M. Koduvely

Learning Bayesian Models with R

  • b8922743533has quoted8 years ago
    The Wishart distribution is a multivariate generalization of the Gamma distribution. It is defined over symmetric non-negative matrix-valued random variables.
  • b8922743533has quoted8 years ago
    The Wishart distribution is a multivariate generalization of the Gamma distribution. It is defined over symmetric non-negative matrix-valued random variables
  • b8922743533has quoted8 years ago
    The Dirichlet distribution is a multivariate analogue of the Beta distribution. It is commonly used in Bayesian inference as the conjugate prior distribution for multinomial distribution and categorical distribution.
  • b8922743533has quoted8 years ago
    another common distribution used in Bayesian inference. It is used for modeling the waiting times such as survival rates
  • b8922743533has quoted8 years ago
    another common distribution used in Bayesian inference. It is used for modeling the waiting times such as survival rate
  • b8922743533has quoted8 years ago
    is another common distribution used in Bayesian inference. It is used for modeling the waiting times such as survival rat
  • b8922743533has quoted8 years ago
    the Beta distribution has been used for modeling allele frequencies in population genetics, time allocation in project management, the proportion of minerals in rocks,
  • b8922743533has quoted8 years ago
    The Beta distribution is a very important distribution in Bayesian inference. It is the conjugate prior probability distribution (which will be defined more precisely in the next chapter) for bino
  • b8922743533has quoted8 years ago
    binomial distribution is a discrete distribution that gives the probability of heads in n independent trials where each trial has one of two possible outcomes, heads or t
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