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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 (38 runs, generated 2026-08-05T22:07:27Z)#

cell sigma M mean se pasts predicted
bp300-6000_s1 1 512 0.9409 0.0064 304 0.9513
bp300-6000_s16 16 512 2.5543 0.0138 304 2.5680
bp300-6000_s2 2 512 1.3177 0.0068 304 1.3319
bp300-6000_s32 32 512 2.9853 0.0294 304 2.9938
bp300-6000_s4 4 512 1.7144 0.0077 304 1.7342
bp300-6000_s8 8 512 2.1316 0.0144 304 2.1476
lp3000_s1 1 512 0.4831 0.0141 304 0.6166
lp3000_s16 16 512 1.4530 0.0106 304 1.4888
lp3000_s2 2 512 0.7539 0.0161 304 0.8251
lp3000_s32 32 512 1.6516 0.0117 304 1.7179
lp3000_s4 4 512 0.9970 0.0103 304 1.0415
lp3000_s8 8 512 1.2190 0.0109 304 1.2632
ma8_s1 1 512 0.4885 0.0123 304 0.6100
ma8_s16 16 512 3.1981 0.0178 304 3.1777
ma8_s2 2 512 0.9724 0.0064 304 0.9825
ma8_s32 32 512 4.0838 0.0145 304 4.1125
ma8_s4 4 512 1.5597 0.0067 304 1.5529
ma8_s8 8 512 2.2940 0.0081 304 2.3064
none_s1 1 512 2.1047 0.0029 304 2.1048
none_s16 16 512 6.0013 0.0224 304 6.0473
none_s2 2 512 3.0627 0.0051 304 3.0620
none_s32 32 512 7.0637 0.0587 304 7.0472
none_s4 4 512 4.0320 0.0076 304 4.0508
none_s8 8 512 5.0671 0.0176 304 5.0480
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