Producing plot "distance to model - error" for applicability domain studies Prediction variance is taken as distance to model
cmf_ecvr_plot_d2m_error(ecvr_fname = "ligands-ecvr.RData", mean_parts = TRUE, nparts = 3, color_parts = "red", ...)
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##---- Should be DIRECTLY executable !! ---- ##-- ==> Define data, use random, ##-- or do help(data=index) for the standard data sets. ## The function is currently defined as function (ecvr_fname = "ligands-ecvr.RData", mean_parts = TRUE, nparts = 3, color_parts = "red", ...) { load(ecvr_fname) y_err <- abs(ecvr$y_exp - ecvr$y_pred_mean) d2m <- ecvr$y_pred_sd cinf_plot_d2m_error(y_err, d2m, mean_parts = mean_parts, nparts = nparts, color_parts = color_parts, ...) }#> function (ecvr_fname = "ligands-ecvr.RData", mean_parts = TRUE, #> nparts = 3, color_parts = "red", ...) #> { #> load(ecvr_fname) #> y_err <- abs(ecvr$y_exp - ecvr$y_pred_mean) #> d2m <- ecvr$y_pred_sd #> cinf_plot_d2m_error(y_err, d2m, mean_parts = mean_parts, #> nparts = nparts, color_parts = color_parts, ...) #> } #> <environment: 0x10fdbe278>