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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 (21 runs, generated 2026-08-03T20:31:12Z)#

cell sigma M mean se pasts predicted
bp300-6000_s1 1 512 0.9430 0.0088 168 0.9513
bp300-6000_s16 16 512 2.5458 0.0178 168 2.5680
bp300-6000_s2 2 512 1.3180 0.0097 168 1.3319
bp300-6000_s32 32 512 2.9432 0.0277 168 2.9938
bp300-6000_s4 4 512 1.7107 0.0100 168 1.7342
bp300-6000_s8 8 512 2.1436 0.0178 168 2.1476
lp3000_s1 1 512 0.4555 0.0185 168 0.6166
lp3000_s16 16 512 1.4517 0.0125 168 1.4888
lp3000_s2 2 512 0.7335 0.0224 168 0.8251
lp3000_s32 32 512 1.6375 0.0156 168 1.7179
lp3000_s4 4 512 1.0161 0.0121 168 1.0415
lp3000_s8 8 512 1.2236 0.0149 168 1.2632
ma8_s1 1 512 0.4866 0.0159 168 0.6100
ma8_s16 16 512 3.2136 0.0257 168 3.1777
ma8_s2 2 512 0.9731 0.0096 168 0.9825
ma8_s32 32 512 4.0845 0.0210 168 4.1125
ma8_s4 4 512 1.5594 0.0093 168 1.5529
ma8_s8 8 512 2.2935 0.0107 168 2.3064
none_s1 1 512 2.1043 0.0040 168 2.1048
none_s16 16 512 5.9808 0.0278 168 6.0473
none_s2 2 512 3.0613 0.0061 168 3.0620
none_s32 32 512 6.9565 0.0570 168 7.0472
none_s4 4 512 4.0380 0.0117 168 4.0508
none_s8 8 512 5.0653 0.0209 168 5.0480
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