rmath.stats

Statistical distributions and summary metrics built for high-throughput data analysis and probabilistic modeling.

Proven: Distributions & Welford's Variance

stats_verify.py

import rmath.array as ra
import rmath.stats as st

# Probability Distributions
norm = st.Normal(0.0, 1.0)
print(f"Normal PDF at 0 : {norm.pdf(0.0):.6f}")

# Numerically stable Welford's Method for Variance
# Even for 1,000,000 elements, variance avoids catastrophic cancellation.
data = ra.randn(1_000_000)
var = data.variance()

print(f"Data Variance   : {var:.6f}")

Normal PDF at 0 : 0.398942 Data Variance : 0.999847