NMath Stats 4.2.0 Full Description
NMath Stats is a .NET statistics library that provides functions for statistical computation and biostatistics, including descriptive statistics, probability distributions, combinatorial functions, multiple linear regression, hypothesis testing, analysis of variance, multivariate statistics, partial least squares, and nonnegative matrix factorization.
NMath Stats is a .NET statistics library containing classes for data manipulation, statistical computation, and biostatistics. Product features include:
A data frame class for holding data of various types (numeric, string, boolean, datetime, and generic), with methods for appending, inserting, removing, sorting, and permuting rows and columns.
Functions for computing descriptive statistics, such as mean, variance, standard deviation, percentile, median, quartiles, geometric mean, harmonic mean, RMS, kurtosis, skewness, and many more.
Special functions, such as factorial, log factorial, binomial coefficient, log binomial, log gamma, incomplete gamma, beta, and incomplete beta.
Probability density function (PDF), cumulative distribution function (CDF), inverse CDF, and random variable moments for a variety of probability distributions, including beta, binomial, chi-square, exponential, F, gamma, geometric, logistic, log-normal, negative binomial, normal (Gaussian), Poisson, Student's t, triangular, and Weibull distributions.
Multiple linear regression.
Basic hypothesis tests, such as z test, t-test, and F-test, with calculation of p-values, critical values, and confidence intervals.
One-way and two-way analysis of variance (ANOVA) and analysis of variance with repeated measures (RANOVA).
Non-parametric tests, such as the Kolmogorov-Smirnov test and Kruskal-Wallis rank sum test.
Multivariate statistical analyses, including principal component analysis, hierarchical cluster analysis, and k-means cluster analysis.
Nonnegative matrix factorization (NMF), and data clustering using NMF.
Partial least squares (PLS), including cross validation and the SIMPLS and NIPALS algorithms.
Data filtering, including a moving average filter and a Savitzky-Golay smoothing filter.
Plotting using the Microsoft Chart Controls for .NET.
Release notes:
New Release
Added two way anova with unbalanced designs
partial least squares discriminant analysis
auxiliary stats for logistic regressions.
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NMath Stats full changelog ]
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