When using OrdPLS(c)predict, it may happen that during cross-validation the data set is split in such a way that two thresholds are exactly equal. This seems to be the case especially with a large number of categories. If two thresholds are exactly equal, this leads to problems when simulating values of the truncated normal distribution for the categorical indicators (line 510).
Idea: We can manually adjust the lower or upper threshold value by 0.0001 so that the two values are no longer exactly equal.
When using OrdPLS(c)predict, it may happen that during cross-validation the data set is split in such a way that two thresholds are exactly equal. This seems to be the case especially with a large number of categories. If two thresholds are exactly equal, this leads to problems when simulating values of the truncated normal distribution for the categorical indicators (line 510). Idea: We can manually adjust the lower or upper threshold value by 0.0001 so that the two values are no longer exactly equal.