Langgartner, Dominik M. Füchsl, Andrea Kaiser, Lisa M. Meier, Tatjana Foertsch, Sandra Buske, Christian O. Reber, Stefan Mulaw, Medhanie A. Biomarkers for classification and class prediction of stress in a murine model of chronic subordination stress - Fig 4 <p>(a) A plot showing null hypothesis distribution generated using Monte Carlo Simulation (blue density and scatter plots) and bootstrap based mean and confidence interval estimation of the prediction error encountered by the tsp model (red density and scatter plots). The x-axis shows the number of iterations/replicates while the y-axis shows the prediction error. Dark blue lines, both in the density plots and scatter plots represents estimated mean of the null hypothesis ( [Ho]). Full red line is the mean prediction error ( [boostrap]) as estimated by the bootstrap analysis while the dashed red lines are the corresponding 95% Confidence Intervals (95% CI [bootstrap]). The black line indicates the empirical prediction error (EPE) obtained in the validation set analysis. (b) A Plot of the statistical significance and confidence interval of the prediction analysis of the SVM model (details of the labels are as described in Fig 4a).</p> body weight gain;tsp;SVM;non-stressed mice;subordination stress Selye;PCA;CSC;SHC;triad;support vector machines;analysis;GC 2018-09-05
    https://plos.figshare.com/articles/figure/Biomarkers_for_classification_and_class_prediction_of_stress_in_a_murine_model_of_chronic_subordination_stress_-_Fig_4/7050245
10.1371/journal.pone.0202471.g004