Comments (1)
Partly implemented.
Based on the current implementation, it would be very interesting to do this multiple times internally and calculate list of zeta score distributions ranked by mean or median, based on such multiple random partitionings of the data, then use this to do significance tests on the zeta scores with meaningfully partitioned data to estimate which zeta scores can actually be considered statistically significant given a certain text collection and partitioning.
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Related Issues (10)
- Add sample input HOT 1
- Require utf-8 input HOT 1
- Add separate howto HOT 1
- Add overall relative frequency to results
- Use overall relative frequency as cutoff for wordlist (parameter)
- Add sampling of n segments from each document HOT 1
- Address deprection warning in calculate.py HOT 2
- Add parameter file
- KeyError: "None of ['idno'] are in the columns" HOT 3
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