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In statistics, the Box–Cox distribution (also known as the power-normal distribution) is the distribution of a random variable X for which the Box–Cox transformation on X follows a truncated normal distribution. It is a continuous probability distribution having probability density function (pdf) given by
In statistics, a power transform is a family of functions applied to create a monotonic transformation of data using power functions.It is a data transformation technique used to stabilize variance, make the data more normal distribution-like, improve the validity of measures of association (such as the Pearson correlation between variables), and for other data stabilization procedures.
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The exponential distribution is recovered as . Originally proposed by the statisticians George Box and David Cox in 1964, [2] and known as the reverse Box–Cox transformation for =, a particular case of power transform in statistics.
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As currently written, the power transform article mentions just the Box-Cox, so a merge/redirect would make sense. However, I think that other article could be improved by generalizing beyond just the Box-Cox (e.g., taking the square root of Poisson data before performing linear regression). Baccyak4H 17:16, 19 July 2007 (UTC)
George Box. The phrase "all models are wrong" was first attributed to George Box in a 1976 paper published in the Journal of the American Statistical Association.In the paper, Box uses the phrase to refer to the limitations of models, arguing that while no model is ever completely accurate, simpler models can still provide valuable insights if applied judiciously. [1]
Box and Cox may refer to: . Box and Cox, a comic play by John Maddison Morton first produced in 1847; Box and Cox Publications, a London music publisher; George Box and Sir David Cox, who devised the Box–Cox transformation to normalise data into a Box–Cox distribution