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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 (23 runs, generated 2026-08-03T23:57:50Z)#

cell sigma M mean se pasts predicted
bp300-6000_s1 1 512 0.9405 0.0084 184 0.9513
bp300-6000_s16 16 512 2.5447 0.0164 184 2.5680
bp300-6000_s2 2 512 1.3181 0.0091 184 1.3319
bp300-6000_s32 32 512 2.9446 0.0265 184 2.9938
bp300-6000_s4 4 512 1.7180 0.0094 184 1.7342
bp300-6000_s8 8 512 2.1432 0.0166 184 2.1476
lp3000_s1 1 512 0.4607 0.0177 184 0.6166
lp3000_s16 16 512 1.4516 0.0124 184 1.4888
lp3000_s2 2 512 0.7420 0.0211 184 0.8251
lp3000_s32 32 512 1.6400 0.0149 184 1.7179
lp3000_s4 4 512 1.0159 0.0117 184 1.0415
lp3000_s8 8 512 1.2192 0.0140 184 1.2632
ma8_s1 1 512 0.4862 0.0153 184 0.6100
ma8_s16 16 512 3.2192 0.0259 184 3.1777
ma8_s2 2 512 0.9746 0.0090 184 0.9825
ma8_s32 32 512 4.0861 0.0194 184 4.1125
ma8_s4 4 512 1.5587 0.0090 184 1.5529
ma8_s8 8 512 2.2965 0.0113 184 2.3064
none_s1 1 512 2.1038 0.0037 184 2.1048
none_s16 16 512 5.9889 0.0291 184 6.0473
none_s2 2 512 3.0642 0.0059 184 3.0620
none_s32 32 512 6.9724 0.0572 184 7.0472
none_s4 4 512 4.0408 0.0110 184 4.0508
none_s8 8 512 5.0595 0.0193 184 5.0480
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