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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 (43 runs, generated 2026-08-06T15:13:43Z)#

cell sigma M mean se pasts predicted
bp300-6000_s1 1 512 0.9368 0.0063 344 0.9513
bp300-6000_s16 16 512 2.5500 0.0125 344 2.5680
bp300-6000_s2 2 512 1.3148 0.0065 344 1.3319
bp300-6000_s32 32 512 2.9770 0.0264 344 2.9938
bp300-6000_s4 4 512 1.7180 0.0072 344 1.7342
bp300-6000_s8 8 512 2.1310 0.0129 344 2.1476
lp3000_s1 1 512 0.4764 0.0130 344 0.6166
lp3000_s16 16 512 1.4575 0.0101 344 1.4888
lp3000_s2 2 512 0.7568 0.0150 344 0.8251
lp3000_s32 32 512 1.6534 0.0109 344 1.7179
lp3000_s4 4 512 0.9989 0.0096 344 1.0415
lp3000_s8 8 512 1.2226 0.0098 344 1.2632
ma8_s1 1 512 0.4895 0.0116 344 0.6100
ma8_s16 16 512 3.1970 0.0165 344 3.1777
ma8_s2 2 512 0.9718 0.0060 344 0.9825
ma8_s32 32 512 4.0803 0.0131 344 4.1125
ma8_s4 4 512 1.5585 0.0060 344 1.5529
ma8_s8 8 512 2.2947 0.0076 344 2.3064
none_s1 1 512 2.1083 0.0048 344 2.1048
none_s16 16 512 6.0122 0.0236 344 6.0473
none_s2 2 512 3.0644 0.0047 344 3.0620
none_s32 32 512 7.0905 0.0558 344 7.0472
none_s4 4 512 4.0353 0.0073 344 4.0508
none_s8 8 512 5.0575 0.0158 344 5.0480
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