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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 (15 runs, generated 2026-08-02T23:47:38Z)#

cell sigma M mean se pasts predicted
bp300-6000_s1 1 512 0.9410 0.0109 120 0.9513
bp300-6000_s16 16 512 2.5407 0.0219 120 2.5680
bp300-6000_s2 2 512 1.3210 0.0120 120 1.3319
bp300-6000_s32 32 512 2.9646 0.0351 120 2.9938
bp300-6000_s4 4 512 1.7123 0.0119 120 1.7342
bp300-6000_s8 8 512 2.1515 0.0231 120 2.1476
lp3000_s1 1 512 0.4697 0.0214 120 0.6166
lp3000_s16 16 512 1.4597 0.0150 120 1.4888
lp3000_s2 2 512 0.7273 0.0261 120 0.8251
lp3000_s32 32 512 1.6346 0.0195 120 1.7179
lp3000_s4 4 512 1.0177 0.0142 120 1.0415
lp3000_s8 8 512 1.2286 0.0176 120 1.2632
ma8_s1 1 512 0.4766 0.0183 120 0.6100
ma8_s16 16 512 3.1945 0.0304 120 3.1777
ma8_s2 2 512 0.9809 0.0113 120 0.9825
ma8_s32 32 512 4.0759 0.0199 120 4.1125
ma8_s4 4 512 1.5592 0.0111 120 1.5529
ma8_s8 8 512 2.3026 0.0133 120 2.3064
none_s1 1 512 2.1033 0.0048 120 2.1048
none_s16 16 512 5.9749 0.0329 120 6.0473
none_s2 2 512 3.0604 0.0058 120 3.0620
none_s32 32 512 7.0064 0.0694 120 7.0472
none_s4 4 512 4.0322 0.0110 120 4.0508
none_s8 8 512 5.0669 0.0259 120 5.0480
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