Dew.Stats.Linux is the Linux-native accelerated edition of the Dew.Stats statistical computing library. It provides a comprehensive suite of tools for probability distributions, hypothesis testing, regression, multivariate analysis, experimental design, and time-series modeling, powered by the high-performance vectorized numerical backend in Dew.Math.Linux. This edition is designed for Linux-based compute servers, HPC pipelines, analytics microservices, research clusters, data acquisition systems, and real-time industrial environments. Statistical Capabilities: - Probability distributions (PDF, CDF, inverse CDF) for 36+ discrete and continuous models - Random number generators and parameter estimation - Descriptive statistics, histograms, ogives, quantiles, outlier analysis Hypothesis Testing and Inference: - Parametric tests (t, Z, F, Chi-Squared, Bartlett, Hotelling T²) - Non-parametric tests (Wilcoxon, Sign, Mann–Whitney, Anderson–Darling, Shapiro–Wilk, KS) - Confidence intervals, residual diagnostics, model fitness evaluation Regression and Statistical Modeling: - Linear, multiple linear, logistic, Poisson, ridge and nonlinear regression - ANOVA and ANCOVA - Principal Component Regression and regularization workflows Multivariate and Structural Analysis: - PCA (correlation/covariance) with eigen decomposition - PCA residuals, factor rotation, Bartlett tests, item analysis - Classical Multidimensional Scaling and dimensionality interpretation Time Series Modeling and Forecasting: - ACF and PACF analysis - ARMA, ARIMA and ARAR models - Exponential smoothing (single/double/triple) - Box-Ljung significance testing and forecasting evaluation High-Level Statistical Workflow Components: - TMtxANOVA, TMtxMulLinReg, TMtxNonLinReg, TMtxPCA, TMtxHypothesisTest, TMtxBinaryTest, TMtxMDScaling Platform Characteristics: - Uses **Dew.Math.Linux** for native BLAS/LAPACK acceleration with AVX2/AVX512 dispatch - Highly scalable under multi-threaded workloads - No Windows or WinForms dependencies - Headless execution suitable for batch, service, and compute-node environments Dew.Stats.Linux provides the full analytical capabilities of Dew.Stats, optimized specifically for Linux-based CPU compute environments.
Get Started
$ dotnet add package Dew.Stats.LinuxReadme
Dew Stats Library for .NET Core
Statistical library built on top of Dew Math Linux Library includes among other features:
- Different probability distributions (PDF, CDF and inverse CDF for 36 distributions), random number generators, parameter estimate.
- Descriptive statistics. Histograms, ogives, cumulative sum, nth moments, percentile, range, IQR, mean, median, mode, ranks and more.
- Multivariate Analysis. PCA by using covariance/correlation matrix, PCA residuals, orthogonal rotation of ZScores, Bartlett test for dimensionality and Z-Scores; Classical Multidimensional Scaling, Hotelling T2 test, M-Box test, Item Analysis.
- Design of Experiment. Full Factorial Design, Latin HyperCube design, ...
- Hypothesis testing. Sign test, Wilcoxon Signed Rank test, one-sample t-test, two-sample paired/unpaired t-test, Z-Test, Chi-Squared test, F-Test, Shapiro-Wilks test, Chi-Squared Goodness of Fit test and Shapiro-Francia test; Berra-Jarque, Anderson-Darling, Kolmogorov-Smirnov test, Mann-Whitney U test, LillioeFors Goodness of Fit test, ...
- Regression models. Linear (weighted, unweighted), Multiple linear (weighted, unweighted), Logistic regression, Ridge regression, Poisson regression, General non-linear regression (using the BFGS, Marquardt, Conjugate gradient or Simplex method), one-way and two-way ANOVA, Principal Component Regression.
- Statistical charts. Optional with separate assembly depending on Steema TeeChart.NET: Probabilities plot (Normal, Weibull, QQ), variable control charts ( X, R, S and EWMA), attribute control charts (P, NP, U and C), dot plot, box plot, biplot, error ellipses PLUS all major statistical chart types, supported by Steema's TeeChart (error, barr, error bar, pie, box, scatter, scatter 3D, histogram, Pareto and more).
- Time series analysis. Sample ACF, PACF, exponential smoothing (single, double, triple), support for ARMA/ARIMA models (simulating, forecasting, estimating coefficients by using Yule-Walker, Burg, Innovations and MLE algorithms), ARAR time series model, moving average, memory-shortening filter, Box-Ljung statistics, etc..
- Ready-to-use components. TMtxANOVA (encapsulates ANOVA routines), TMtxMulLinReg (encapsulates multiple linear regression routines), TMtxNonLinReg (encapsulates nonlinear regression routines), TMtxPCA (encapsulates PCA routines), TMtxHypothesisTest (encapsulates hypothesis testing routines), TMtxBinaryTest (encapsulates binary diagonstic test routines), TMtxMDScaling (encapsulates multimensional scaling routines).