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• Bayesian Phylogenetic Analysis
  ...ning the '''likelihood''' and the '''[[Prior probability|prior probability distribution]]'''. ...sian approach still allows one to interpret the posterior as a probability distribution. If the prior is NOT flat, then it may have a substantial impact on the pos
  28 KB (4,371 words) - 03:28, 14 April 2008
• Markov chain Monte Carlo
  ...in after a large number of steps is then used as a sample from the desired distribution. The quality of the sample improves as a function of the number of steps. ...acceptable error. A good chain will have rapid mixing—the stationary distribution is reached quickly starting from an arbitrary position. Tools for proving r
  6 KB (864 words) - 00:50, 30 December 2005
• Posterior probability
  ...rior probability''' can be calculated by [[Bayes' theorem]] from the prior probability and the [[likelihood function]]. ...iven the data. It can be calculated by multiplying the [[prior probability distribution]] by the [[likelihood function]], and then dividing by the [[normalizing co
  1 KB (194 words) - 22:54, 29 December 2005
• Prior probability
  A '''prior probability''' is a [[conditional probability|marginal probability]], interpreted as a description of what is known about a variable in the ab The ''[[posterior probability]]'' is then the [[conditional probability]] of the variable taking the evidence into account.
  12 KB (1,800 words) - 22:58, 29 December 2005
• Maximum likelihood
  ...d used to make inferences about parameters of the underlying [[probability distribution]] of a given [[data set]]. ...notions in [[probability theory]] such as [[probability distribution]]s, [[probability density function]]s, [[random variable]]s and [[expected value|expectation]
  5 KB (832 words) - 04:49, 13 September 2006
• Maximum a posteriori
  ...t employs an augmented optimization objective which incorporates a [[prior distribution]] over the quantity one wants to estimate. MAP estimation can therefore be # Analytically, when the mode(s) of the posterior distribution can be given in [[closed-form solution|closed form]]. This is the case whe
  2 KB (305 words) - 23:05, 29 December 2005
• Marginal distribution
  ..., typically calculated by summing or integrating the [[joint probability]] distribution over ''Y''. For [[discrete random variable]]s, the [[marginal probability]] mass function can be written as Pr(''X'' = ''x''). This is
  2 KB (261 words) - 23:10, 29 December 2005
• Metropolis-coupled Markov chain Monte Carlo
  ...e heat value of the chain. Heating a Markov chain increases the acceptance probability of new states. A heated chain tends to accept more states than a cold chain ...sup>3</sup> can be used to empirically determine the posterior probability distribution of trees, branch lengths, and substitution parameters.
  3 KB (386 words) - 00:37, 30 December 2005
• Inferring Phylogenies
  <li>Logical probability?</li> <li>Distribution of rates</li>
  20 KB (3,034 words) - 10:55, 6 January 2006
• Z-Hunt
  ...y of a given sequence to adopt the left-handed form of DNA; it is simply a probability score. ...ping Z-DNA in the human genome. Computer-aided mapping reveals a nonrandom distribution of potential Z-DNA-forming sequences in human genes. ''J Biol Chem, 267(17)
  8 KB (1,042 words) - 01:03, 23 January 2015
• Diehard tests
  ...acings between the points should be asymptotically [[wikipedia:exponential distribution|exponentially distributed]].<ref>Renyi, 1953, p194</ref> The name is based ...numbers. The 120 possible orderings should occur with statistically equal probability.
  4 KB (528 words) - 19:35, 11 October 2015
• Python/SciPy
  ; Gaussian [[:wikipedia:Probability density function|probability density function]] (PDF) ; Guassian [[:wikipedia:Cumulative distribution function|cumulative distribution function]] (CDF)
  3 KB (458 words) - 23:53, 30 March 2017