This version can be pinned in stack with:tdigest-0.3@sha256:cb708b3f1cfb19722b5eb80a4afcf6db36da4ad07a68fe0c865e2361db0b95dd,2931
Module documentation for 0.3
tdigest
A new data structure for accurate on-line accumulation of rank-based statistics such as quantiles and trimmed means.
See original paper: “Computing extremely accurate quantiles using t-digest” by Ted Dunning and Otmar Ertl
Synopsis
λ *Data.TDigest > median (tdigest [1..1000] :: TDigest 3)
Just 499.0090729817737
Benchmarks
Using 50M exponentially distributed numbers:
- average: 16s; incorrect approximation of median, mostly to measure prng speed
 
- sorting using 
vector-algorithms: 33s; using 1000MB of memory 
- sparking t-digest (using some 
par): 53s 
- buffered t-digest: 68s
 
- sequential t-digest: 65s
 
Example histogram
tdigest-simple -m tdigest -d standard -s 100000 -c 10 -o output.svg -i 34
cp output.svg example.svg
inkscape --export-png=example.png --export-dpi=80 --export-background-opacity=0 --without-gui example.svg

0.3
- Depend on 
foldable1-classes-compat instead of semigroupoids. 
0.2.1.1
0.2.1
- Add size, valid, validate, and debugPrint for NonEmpty
#26
 
0.2
- Add 
Data.TDigest.Vector module. 
0.1
- Add 
validateHistogram and debugPrint 
- Fix a pointy centroid bug.
 
- Add 
Data.TDigest.NonEmpty module 
- Add 
mean, variance, stddev