classify: Calculate Classification Statistics
In classify: Classification Accuracy and Consistency under IRT models.

Internal function to calculate classification statistics.

1	classify(cssd, expected, bnds, cats, lbls=NULL)

`cssd`	Conditional Summed Score Distribution
`expected`	Numeric vector of Expected Scores
`bnds`	Numeric vector of grade boundaries, specified in ascending order, including the minimum and maximum mark on the test.
`cats`	Numeric vector of item categories.
`lbls`	Character vector of grade labels. Optional.

List of classification statistics:
Candidate level accuracy
Candidate level false negatives
Candidate level false positives
Summary of consistency
Matrix of grade probability combinations
Kappa
Candidate level classification consistency
Summary of accuracy by grade
Summary of false positives by grade
Summary of false negatives by grade
Summary of consistency by grade