Regularized canonical correlation models improve prediction of weather impacts on semen quality in Murciano-Granadina bucks.

The robustness of the model was further supported by multivariate test statistics, including Pillai’s trace, Hotelling–Lawley trace, Roy’s greatest root, and Wilks’ Lambda, all of which were highly significant (p < 0.0001), confirming the presence of a statistically meaningful association between the two variable sets.

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