![]() ![]() , probs = quantile )) %>% summarise ( mean_thresh = mean ( perm_thresh, na. ![]() Click on the Import Dataset tab, choose from Text (base)., and select. permimpapplies a different implementation for the CPI, in order to mitigate some issues related to the implementation of the CPI in the party-package. id = "permutation" ) } perm_summarise % group_by ( permutation ) %>% summarise ( perm_thresh = as.vector ( stability ) %>% ecdf () %>% quantile (. Alternatively, since R provides intrinsic function var.test() for the F test. The permimp-package is developed to replace the Conditional Permutation Importance (CPI) computation by the varimp-function(s) of the party-package. , data = data, outcome = outcome, boot_reps = perm_boot_reps ). id = "bootstrap" )) %>% select ( - splits ) %>% unnest ( perm_coefs ) %>% filter ( variable != "(Intercept)" ) %>% select ( - id ) %>% group_by ( permutation ) %>% nest () %>% rename ( perm_data = data ) %>% map_df (. id = "permutation" ) } perm_model % mutate ( perm_coefs = map (. #' internal #' dplyr #' purrr map #' tidyr unnest #' utils globalVariables #' rsample permutations #' utils :: globalVariables ( c ( "stab_df", "perm_thresh", "mean_thresh", "perm_coefs", "perm_stabs", "splits", "permutation" )) perm_sample % map_df (. R/bartpackagepredicts.R defines the following functions: calcpredictionintervals calccredibleintervals bartmachinegetposterior bartpredictfortestdata labelstoylevels predict. "y") #' permutations the number of times to be permuted per repeat #' perm_boot_reps the number of times to repeat each set of permutations #' quantile The quantile of null stabilities to use as a threshold. #' #' data a dataframe containing an outcome variable to be permuted #' outcome the outcome to be permuted as a string (i.e. We could use a reproducible example or screenshot of your R session with the plot window. ![]() In any case, your description is insufficient to diagnose the problem. This can happen if you have a small plot window. #' permute #' #' permute #' #' Calculates permutation threshold for null model, where a specified model is run over multiple bootstrap resamples of multiple permuted version of the dataset. Margins appear to be too large for your image. ![]()
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