Estimation of Transformations for Microarray Data Using Maximum Likelihood and Related Methods
نویسندگان
چکیده
Motivation and Results Durbin et al (2002), Huber et al (2002) and Munson (2001) independently introduced a family of transformations (the generalized-log family) which stabilizes the variance of microarray data up to the first order. We introduce a method for estimating the transformation parameter in tandem with a linear model based on the procedure outlined in Box and Cox (1964). We also discuss means of finding transformations within the generalized-log family which are optimal under other criteria, such as minimum residual skewness and minimum mean-variance dependency. Contact. [email protected]
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