📊 Statistics & Data
Perform distributions, hypothesis testing, regression, and data analysis directly in CSharpNumerics.
namespace CSharpNumerics.Statistics
| Module | Description |
|---|---|
| 📏 Descriptive | Summary statistics, moments, percentiles, skewness, and kurtosis |
| 📈 Inferential | Regression, correlation, estimation, and inferential analysis |
| 🧪 Hypothesis Testing | Parametric and non-parametric tests, ANOVA, and significance workflows |
| 🎲 Random | Seedable random-number generation and advanced sampling methods |
| 🔔 Distributions | Probability distributions, density functions, and shared distribution interfaces |
| 🎯 Monte Carlo | General-purpose Monte Carlo simulation and stochastic estimation |
| 🛡️ Robust | Outlier-resistant statistical methods |
| ⤴️ Curve Fitting | Curve fitting, residual analysis, goodness-of-fit, and parameter estimation |
| ⏳ Time Series Analysis | Periodic signal detection, detrending, phase folding, peak fitting, and Holt–Winters forecasting |
| ≈ State Estimation | Kalman filter, extended Kalman filter, and Rauch–Tung–Striebel smoother |
| 🗃️ Data | Indexed datasets, time-series structures, and statistical data containers |