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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 (10 runs, generated 2026-08-02T14:34:17Z)#

cell sigma M mean se pasts predicted
bp300-6000_s1 1 512 0.9405 0.0147 80 0.9513
bp300-6000_s16 16 512 2.5421 0.0269 80 2.5680
bp300-6000_s2 2 512 1.3372 0.0150 80 1.3319
bp300-6000_s32 32 512 2.9281 0.0449 80 2.9938
bp300-6000_s4 4 512 1.7071 0.0160 80 1.7342
bp300-6000_s8 8 512 2.1471 0.0276 80 2.1476
lp3000_s1 1 512 0.4688 0.0258 80 0.6166
lp3000_s16 16 512 1.4637 0.0202 80 1.4888
lp3000_s2 2 512 0.7469 0.0316 80 0.8251
lp3000_s32 32 512 1.6358 0.0278 80 1.7179
lp3000_s4 4 512 1.0216 0.0184 80 1.0415
lp3000_s8 8 512 1.2288 0.0197 80 1.2632
ma8_s1 1 512 0.4786 0.0216 80 0.6100
ma8_s16 16 512 3.1847 0.0396 80 3.1777
ma8_s2 2 512 0.9738 0.0100 80 0.9825
ma8_s32 32 512 4.0471 0.0178 80 4.1125
ma8_s4 4 512 1.5605 0.0134 80 1.5529
ma8_s8 8 512 2.2991 0.0163 80 2.3064
none_s1 1 512 2.0979 0.0050 80 2.1048
none_s16 16 512 6.0041 0.0377 80 6.0473
none_s2 2 512 3.0598 0.0073 80 3.0620
none_s32 32 512 7.0043 0.0876 80 7.0472
none_s4 4 512 4.0364 0.0152 80 4.0508
none_s8 8 512 5.0760 0.0327 80 5.0480
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