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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 (11 runs, generated 2026-08-02T15:53:59Z)#

cell sigma M mean se pasts predicted
bp300-6000_s1 1 512 0.9454 0.0136 88 0.9513
bp300-6000_s16 16 512 2.5361 0.0250 88 2.5680
bp300-6000_s2 2 512 1.3366 0.0140 88 1.3319
bp300-6000_s32 32 512 2.9402 0.0423 88 2.9938
bp300-6000_s4 4 512 1.7086 0.0149 88 1.7342
bp300-6000_s8 8 512 2.1477 0.0252 88 2.1476
lp3000_s1 1 512 0.4648 0.0240 88 0.6166
lp3000_s16 16 512 1.4675 0.0189 88 1.4888
lp3000_s2 2 512 0.7513 0.0295 88 0.8251
lp3000_s32 32 512 1.6352 0.0257 88 1.7179
lp3000_s4 4 512 1.0189 0.0171 88 1.0415
lp3000_s8 8 512 1.2293 0.0186 88 1.2632
ma8_s1 1 512 0.4832 0.0214 88 0.6100
ma8_s16 16 512 3.1783 0.0362 88 3.1777
ma8_s2 2 512 0.9723 0.0093 88 0.9825
ma8_s32 32 512 4.0514 0.0174 88 4.1125
ma8_s4 4 512 1.5612 0.0133 88 1.5529
ma8_s8 8 512 2.2962 0.0151 88 2.3064
none_s1 1 512 2.0976 0.0047 88 2.1048
none_s16 16 512 6.0135 0.0381 88 6.0473
none_s2 2 512 3.0575 0.0069 88 3.0620
none_s32 32 512 6.9959 0.0804 88 7.0472
none_s4 4 512 4.0343 0.0140 88 4.0508
none_s8 8 512 5.0705 0.0309 88 5.0480
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