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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 (17 runs, generated 2026-08-03T08:16:29Z)#

cell sigma M mean se pasts predicted
bp300-6000_s1 1 512 0.9419 0.0101 136 0.9513
bp300-6000_s16 16 512 2.5446 0.0206 136 2.5680
bp300-6000_s2 2 512 1.3240 0.0112 136 1.3319
bp300-6000_s32 32 512 2.9592 0.0324 136 2.9938
bp300-6000_s4 4 512 1.7080 0.0107 136 1.7342
bp300-6000_s8 8 512 2.1493 0.0214 136 2.1476
lp3000_s1 1 512 0.4590 0.0206 136 0.6166
lp3000_s16 16 512 1.4579 0.0140 136 1.4888
lp3000_s2 2 512 0.7242 0.0244 136 0.8251
lp3000_s32 32 512 1.6416 0.0179 136 1.7179
lp3000_s4 4 512 1.0254 0.0129 136 1.0415
lp3000_s8 8 512 1.2278 0.0157 136 1.2632
ma8_s1 1 512 0.4860 0.0178 136 0.6100
ma8_s16 16 512 3.2061 0.0286 136 3.1777
ma8_s2 2 512 0.9754 0.0108 136 0.9825
ma8_s32 32 512 4.0796 0.0181 136 4.1125
ma8_s4 4 512 1.5573 0.0102 136 1.5529
ma8_s8 8 512 2.2975 0.0123 136 2.3064
none_s1 1 512 2.1039 0.0045 136 2.1048
none_s16 16 512 5.9987 0.0327 136 6.0473
none_s2 2 512 3.0553 0.0056 136 3.0620
none_s32 32 512 7.0015 0.0645 136 7.0472
none_s4 4 512 4.0406 0.0138 136 4.0508
none_s8 8 512 5.0624 0.0235 136 5.0480
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