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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 (24 runs, generated 2026-08-04T04:22:31Z)#

cell sigma M mean se pasts predicted
bp300-6000_s1 1 512 0.9412 0.0082 192 0.9513
bp300-6000_s16 16 512 2.5422 0.0160 192 2.5680
bp300-6000_s2 2 512 1.3195 0.0090 192 1.3319
bp300-6000_s32 32 512 2.9770 0.0413 192 2.9938
bp300-6000_s4 4 512 1.7215 0.0097 192 1.7342
bp300-6000_s8 8 512 2.1433 0.0160 192 2.1476
lp3000_s1 1 512 0.4637 0.0176 192 0.6166
lp3000_s16 16 512 1.4483 0.0119 192 1.4888
lp3000_s2 2 512 0.7421 0.0207 192 0.8251
lp3000_s32 32 512 1.6410 0.0144 192 1.7179
lp3000_s4 4 512 1.0198 0.0114 192 1.0415
lp3000_s8 8 512 1.2221 0.0140 192 1.2632
ma8_s1 1 512 0.4898 0.0152 192 0.6100
ma8_s16 16 512 3.2166 0.0249 192 3.1777
ma8_s2 2 512 0.9725 0.0088 192 0.9825
ma8_s32 32 512 4.0841 0.0187 192 4.1125
ma8_s4 4 512 1.5593 0.0087 192 1.5529
ma8_s8 8 512 2.3005 0.0114 192 2.3064
none_s1 1 512 2.1044 0.0037 192 2.1048
none_s16 16 512 5.9938 0.0285 192 6.0473
none_s2 2 512 3.0627 0.0058 192 3.0620
none_s32 32 512 6.9767 0.0558 192 7.0472
none_s4 4 512 4.0413 0.0106 192 4.0508
none_s8 8 512 5.0626 0.0192 192 5.0480
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