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timeseries-entropy / README.md
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Cached entropy estimates#

Machine-generated by .github/workflows/estimates.yml on main — do not edit by hand. Every dispatch runs the whole grid again with fresh, independent pasts, appends one record per cell to runs.jsonl, and rebuilds estimates.json from the full log, so the means tighten run after run.

The estimand is H(z_(M+1) | z_1..z_M) in bits/sample — an upper bound on the entropy rate of z that tightens as the conditioning window M grows.

Fetch it from a browser or a script (raw.githubusercontent.com sends access-control-allow-origin: *):

https://raw.githubusercontent.com/concept-collection/timeseries-entropy/estimates/estimates.json

Current state (13 runs, generated 2026-08-02T19:58:29Z)#

cell sigma M mean se pasts predicted
bp300-6000_s1 1 512 0.9430 0.0121 104 0.9513
bp300-6000_s16 16 512 2.5324 0.0223 104 2.5680
bp300-6000_s2 2 512 1.3242 0.0132 104 1.3319
bp300-6000_s32 32 512 2.9586 0.0385 104 2.9938
bp300-6000_s4 4 512 1.7080 0.0133 104 1.7342
bp300-6000_s8 8 512 2.1573 0.0264 104 2.1476
lp3000_s1 1 512 0.4661 0.0231 104 0.6166
lp3000_s16 16 512 1.4591 0.0168 104 1.4888
lp3000_s2 2 512 0.7351 0.0281 104 0.8251
lp3000_s32 32 512 1.6324 0.0221 104 1.7179
lp3000_s4 4 512 1.0172 0.0154 104 1.0415
lp3000_s8 8 512 1.2347 0.0188 104 1.2632
ma8_s1 1 512 0.4799 0.0198 104 0.6100
ma8_s16 16 512 3.1912 0.0328 104 3.1777
ma8_s2 2 512 0.9765 0.0084 104 0.9825
ma8_s32 32 512 4.0749 0.0212 104 4.1125
ma8_s4 4 512 1.5602 0.0116 104 1.5529
ma8_s8 8 512 2.2995 0.0144 104 2.3064
none_s1 1 512 2.1001 0.0046 104 2.1048
none_s16 16 512 5.9855 0.0355 104 6.0473
none_s2 2 512 3.0568 0.0062 104 3.0620
none_s32 32 512 6.9834 0.0744 104 7.0472
none_s4 4 512 4.0318 0.0123 104 4.0508
none_s8 8 512 5.0569 0.0272 104 5.0480
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