Skip to main content

microprediction/precise

SkillsMP has collected 6 skills from microprediction/precise. Open a skill to review its source and details.

Latest recorded source activity
SkillsMP catalog refreshed
skills collected
6
GitHub stars
333
GitHub forks
58

Skills in this repository

2 occupation categories · 100% classified

Showing 6 of 6 collected skills.

occupation
Data Scientists
description

Online (incremental) covariance, correlation, and precision estimation in Python — the streaming complement to sklearn.covariance. Use when code needs a covariance/correlation matrix updated per observation, recomputes np.cov/np.corrcoef in a rolling loop,…

updated
occupation
Data Scientists
description

Rigorously and honestly assess a NEW or proposed covariance / correlation / precision estimator, or a new covariance scoring rule, using precise. Use when someone proposes, asks to evaluate, or wants to compare a covariance methodology. Covers implementing it…

updated
occupation
Data Scientists
description

Pick which precise covariance estimator to use for a given dataset. Use when you have data X and are unsure which estimator fits its dimension, conditioning, or tail behavior. Wraps precise.suggest() and covariance_features().

updated
occupation
Software Developers
description

Estimate a covariance / correlation / precision matrix incrementally with precise. Use when data arrives as a stream and you want the matrix updated per observation, or when you want an online (partial_fit) drop-in for sklearn.covariance, which is batch-only.

updated
occupation
Software Developers
description

Maintain an online covariance over named series whose set changes over time (e.g. assets entering and leaving). Use when observations arrive as dicts keyed by name rather than fixed-length vectors. Wraps precise's keyed / FixedUniverse / DynamicUniverse…

updated
occupation
Software Developers
description

Score and compare covariance estimates with precise's assessor panel. Use when you need to judge an estimate out-of-sample or rank competing estimators — and especially in high dimensions, where the plain held-out likelihood is misleading.

updated
Showing 6 of 6 collected skills.