| t-digest |
| -------- |
| |
| .. currentmodule:: datasketches |
| |
| The implementation in this library is based on the MergingDigest described in |
| `Computing Extremely Accurate Quantiles Using t-Digests <https://arxiv.org/abs/1902.04023>`_ by Ted Dunning and Otmar Ertl. |
| |
| The implementation in this library has a few differences from the reference implementation associated with that paper: |
| |
| * Merge does not modify the input |
| * Derialization similar to other sketches in this library, although reading the reference implementation format is supported |
| |
| Unlike all other algorithms in the library, t-digest is empirical and has no mathematical basis for estimating its error |
| and its results are dependent on the input data. However, for many common data distributions, it can produce excellent results. |
| t-digest also operates only on numeric data and, unlike the the quantiles family algorithms in the library which return quantile |
| approximations from the input domain, t-digest interpolates values and will hold and return data points not seen in the input. |
| |
| The closest alternative to t-digest in this library is REQ sketch. It prioritizes one chosen side of the rank domain: |
| either low rank accuracy or high rank accuracy. t-digest (in this implementation) prioritizes both ends of the rank domain |
| and has lower accuracy towards the middle of the rank domain (median). |
| |
| Measurements show that t-digest is slightly biased (tends to underestimate low ranks and overestimate high ranks), while still |
| doing very well close to the extremes. The effect seems to be more pronounced with more input values. |
| |
| .. autoclass:: tdigest_float |
| :members: |
| :undoc-members: |
| :exclude-members: deserialize |
| |
| .. rubric:: Static Methods: |
| |
| .. automethod:: deserialize |
| |
| .. rubric:: Non-static Methods: |
| |
| .. automethod:: __init__ |
| |
| .. autoclass:: tdigest_double |
| :members: |
| :undoc-members: |
| :exclude-members: deserialize |
| |
| .. rubric:: Static Methods: |
| |
| .. automethod:: deserialize |
| |
| .. rubric:: Non-static Methods: |
| |
| .. automethod:: __init__ |
