Abstract
We employ the modern notation of the multivariate normal distribution. Let x = (x1, . . ., x m ) be a vector of normally correlated random variables with density
where μ is the vector of expectations and A a positive definite m×m matrix.
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© 2007 Springer Science+Business Media, LLC
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(2007). Normal Correlation and Regression. In: A History of Parametric Statistical Inference from Bernoulli to Fisher, 1713–1935. Sources and Studies in the History of Mathematics and Physical Sciences. Springer, New York, NY. https://doi.org/10.1007/978-0-387-46409-1_16
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DOI: https://doi.org/10.1007/978-0-387-46409-1_16
Publisher Name: Springer, New York, NY
Print ISBN: 978-0-387-46408-4
Online ISBN: 978-0-387-46409-1
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