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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 (32 runs, generated 2026-08-05T04:21:47Z)#

cell sigma M mean se pasts predicted
bp300-6000_s1 1 512 0.9383 0.0067 256 0.9513
bp300-6000_s16 16 512 2.5395 0.0136 256 2.5680
bp300-6000_s2 2 512 1.3209 0.0075 256 1.3319
bp300-6000_s32 32 512 2.9772 0.0324 256 2.9938
bp300-6000_s4 4 512 1.7147 0.0084 256 1.7342
bp300-6000_s8 8 512 2.1408 0.0166 256 2.1476
lp3000_s1 1 512 0.4730 0.0156 256 0.6166
lp3000_s16 16 512 1.4538 0.0101 256 1.4888
lp3000_s2 2 512 0.7486 0.0176 256 0.8251
lp3000_s32 32 512 1.6545 0.0131 256 1.7179
lp3000_s4 4 512 1.0036 0.0109 256 1.0415
lp3000_s8 8 512 1.2189 0.0124 256 1.2632
ma8_s1 1 512 0.4813 0.0130 256 0.6100
ma8_s16 16 512 3.1956 0.0194 256 3.1777
ma8_s2 2 512 0.9741 0.0072 256 0.9825
ma8_s32 32 512 4.0748 0.0152 256 4.1125
ma8_s4 4 512 1.5601 0.0075 256 1.5529
ma8_s8 8 512 2.2944 0.0091 256 2.3064
none_s1 1 512 2.1058 0.0032 256 2.1048
none_s16 16 512 6.0010 0.0249 256 6.0473
none_s2 2 512 3.0627 0.0053 256 3.0620
none_s32 32 512 7.0283 0.0516 256 7.0472
none_s4 4 512 4.0368 0.0086 256 4.0508
none_s8 8 512 5.0638 0.0163 256 5.0480
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