An Analysis of Transformations

George E. P. Box; David R. Cox · Journal of the Royal Statistical Society Series B (Statistical Methodology) · 1964

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Author / responsible party

George E. P. Box; David R. Cox

Publisher

Journal of the Royal Statistical Society Series B (Statistical Methodology)

Year

1964

Language

English

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Summary In the analysis of data it is often assumed that observations y 1, y 2, …, yn are independently normally distributed with constant variance and with expectations specified by a model linear in a set of parameters θ. In this paper we make the less restrictive assumption that such a normal, homoscedastic, linear model is appropriate after some suitable transformation has been applied to the y's. Inferences about the transformation and about the parameters of the linear model are made by computing the likelihood function and the relevant posterior distribution. The contributions of normality, homoscedasticity and additivity to the transformation are separated. The relation of the present methods to earlier procedures for finding transformations is discussed. The methods are illustrated with examples.

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APA 7

Box, G. E. P. & Cox, D. R. (1964). An Analysis of Transformations. https://doi.org/10.1111/j.2517-6161.1964.tb00553.x

MLA

Box, George E. P, and David R. Cox. "An Analysis of Transformations." 1964. https://doi.org/10.1111/j.2517-6161.1964.tb00553.x.

Chicago

Box, George E. P. and David R. Cox. 1964. "An Analysis of Transformations.". https://doi.org/10.1111/j.2517-6161.1964.tb00553.x.

Harvard

Box, G. E. P. and Cox, D. R. 1964, An Analysis of Transformations, Journal of the Royal Statistical Society Series B (Statistical Methodology), available at: https://doi.org/10.1111/j.2517-6161.1964.tb00553.x [Accessed 6 Aug. 2026].

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Resource details

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Title: An Analysis of Transformations

Author / contributors: George E. P. Box; David R. Cox

Publisher: Journal of the Royal Statistical Society Series B (Statistical Methodology)

Publication year: 1964

Language: English

Subjects

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Homoscedasticity; Transformation (genetics); Normality; Applied mathematics; Additive function; Mathematics; Constant (computer programming); Data transformation; Set (abstract data type); Linear map; Linear model; Variance (accounting)