Crate stochastic_rs_stats 

stochastic-rs-stats

Statistical estimators for stochastic processes.

Re-exports

pub use stochastic_rs_distributions as distributions;

pub use stochastic_rs_stochastic as stochastic;

Modules

bayesian_diffusion

Bayesian calibration of mean-reverting diffusions

cir

Cir

double_exp

Double Exp

econometrics

Econometrics

filtering

Bayesian Filtering & Sampling

fou_estimator

fOU Estimator

fractal_dim

Fractal dimension estimators

gaussian_kde

Gaussian Kde

gmm_cir

GMM estimator for the CIR / Heston-variance process

heston_mle

Mle

heston_nml_cekf

Heston NMLE-CEKF

hurst

Hurst exponent estimators

leverage

Leverage

mle

Maximum Likelihood Estimation for 1-D Diffusions

non_central_chi_squared

Non Central Chi Squared

normality

Normality tests

particle_mle

Particle-filter maximum likelihood for stochastic volatility

qmle

Quasi-Maximum Likelihood Estimation (QMLE) for diffusions

realized

Realized Volatility & Microstructure-Noise Estimators

simd_rng

SIMD-accelerated random number generation

spectral

Spectral analysis utilities (periodogram and FFT-based spectrum search).

tail_index

Tail Index

traits

Re-exports of upstream traits so crate::traits::Foo continues to resolve inside the stats sub-crate’s source files. Plus the local HypothesisTest trait that unifies hypothesis-test result types.

Macros

py_distribution

py_process_1d