Factorizing Yields in Buchwald-Hartwig Amination

04 August 2023, Version 1
This content is a preprint and has not undergone peer review at the time of posting.

Abstract

The data collected in (1) are revisited and rigorously analyzed. We show that the matrix of descriptors used in the analysis of (1) is up to a linear transformation equivalent to a dummy coded matrix that reflects the design of the underlined experiment. Furthermore, it is argued that the reaction yield is better be modeled as a continuous Bernoulli random variable. Finally, a four-way ANOVA model with single replicates following a continuous Bernoulli distribution is fitted to the data under the assumption of the sparsity of the parameters, and estimated parameters are interpreted. Thereby, a novel regularisation technique based on the partial least squares algorithm is applied.

Keywords

Machine Learning
ANOVA
Continuous Bernoulli
C-N cross-coupling

Supplementary materials

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Description
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Title
Supplementary material for Factorizing Yields in Buchwald-Hartwig Amination
Description
Methods and numerical analysis, Figures S1 to S4, References.
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