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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 (8 runs, generated 2026-08-02T10:40:14Z)#

cell sigma M mean se pasts predicted
bp300-6000_s1 1 512 0.9427 0.0160 64 0.9513
bp300-6000_s16 16 512 2.5417 0.0308 64 2.5680
bp300-6000_s2 2 512 1.3366 0.0183 64 1.3319
bp300-6000_s32 32 512 2.9232 0.0525 64 2.9938
bp300-6000_s4 4 512 1.7218 0.0164 64 1.7342
bp300-6000_s8 8 512 2.1517 0.0337 64 2.1476
lp3000_s1 1 512 0.4877 0.0299 64 0.6166
lp3000_s16 16 512 1.4483 0.0228 64 1.4888
lp3000_s2 2 512 0.7395 0.0368 64 0.8251
lp3000_s32 32 512 1.6310 0.0273 64 1.7179
lp3000_s4 4 512 1.0164 0.0212 64 1.0415
lp3000_s8 8 512 1.2145 0.0231 64 1.2632
ma8_s1 1 512 0.4787 0.0240 64 0.6100
ma8_s16 16 512 3.2010 0.0488 64 3.1777
ma8_s2 2 512 0.9723 0.0121 64 0.9825
ma8_s32 32 512 4.0590 0.0213 64 4.1125
ma8_s4 4 512 1.5639 0.0152 64 1.5529
ma8_s8 8 512 2.2978 0.0180 64 2.3064
none_s1 1 512 2.0945 0.0053 64 2.1048
none_s16 16 512 5.9898 0.0443 64 6.0473
none_s2 2 512 3.0589 0.0084 64 3.0620
none_s32 32 512 6.9423 0.0954 64 7.0472
none_s4 4 512 4.0305 0.0175 64 4.0508
none_s8 8 512 5.0811 0.0383 64 5.0480
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