NMath Stats 3.5.0

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NMath Stats is a useful application that provides classes for data manipulation, statistical computation and biostatistics.

NMath Stats contains a data table class with functions for computing descriptive statistics, such as mean, variance, standard deviation, percentile, median, quartiles, geometric mean, harmonic mean, RMS, kurtosis, skewness and many more. Here are some key features of "NMath Stats":

· 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.
Requirements:

· Microsoft .NET Framework
· NMath Core
Limitations:

· 30 days trial What's New in This Release: [ read full changelog ]

· Upgraded to Intel MKL 10.3 Update 11 with resulting performance increases.
· Added class NMathConfiguration for controlling the loading of the NMath
· license key, kernel assembly, and native library. License files are no
· longer used. Logging can be enabled for debugging configuration issues.
· See Chp 1 in the NMath User's Guide for more information.
· Replaced all custom NMath delegate types in the API with Func/Action
· equivalents, and deprecated the older signatures.
· Added classes DoubleFactorAnalysis, FactorAnalysisCorrelation,
· FactorAnalysisCovariance, and supporting types for performing factor
· analysis.
· Added NMathFunctions.FishersExactTest() for computing the Fisher's Exact
· Test p-value for a specified 2 x 2 contingency table.
· Added class OneSampleAndersonDarlingTest for performing an Anderson-Darling
· test of the distribution of one sample.
· Added class ShapiroWilkTest for testing the null hypothesis that a sample
· comes from a normally distributed population.