CSV import / export, descriptive stats (mean, standard deviation and variance), probability distributions, hypothesis tests, chi-square and student's T-test, linear regression and correlation, random number generators and analysis of variance (ANOVA).
Version: 1.0.1The Statsar statistics library allows you to add high-performance statistics calculations to your .NET platform applications.
License: Free To Try $495.00
Operating System: Windows
The object-oriented library was designed and implemented by numerical experts with proven expertise in the financial industry.
Providing a simple and intuitive object model, the library allows you to rapidly analyze your data by importing familiar data objects such as ADO.NET data tables.
A powerful and robust CSV reader is also included with the component, allowing you to work with existing data files. Bind to virtually any data source including standard data objects, arrays, lists or your own object model.
Sort and reorder data according to complex criteria. Multiple data filters are included, providing a powerful way to remove unwanted or missing values.
Descriptive statistics: count, sum, min, max, mean, mode, median, standard deviation and variance. Ranks, percentiles and interquartile range. Central moments: skew and kurtosis.
Multiple probability distributions including: binomial, negative binomial, Laplace, Poisson, chi-squared, beta, gamma, F, normal, lognormal and student's T.
Random number generators including Mersenne twister pseudorandom numbers. Linear regression with least squares minimization. T-test, Z-test, Kolmogorov-Smirnov test including one sample and two sample testing.
Anaylsis of variance (ANOVA) including RANOVA and one way and two way testing.
Calculating statistics with the Statsar library is easy and you can get started in a few minutes. The download includes a user guide, reference manual and over 25 examples in C# and VB.NET.
Version 1.0.1: Support for new quantile types (weighted averages, closest observation, empirical distribution, empirical distribution averaged) and weighted percentiles.