NMath Stats

July Release of NMath and NMath Stats

Posted on by Paul Shirkey
We are currently working hard on our upcoming July release of our NMath and NMath Stats C# math libraries. This release will add many new features from Runge-Kutta to automatic Peak Finding algorithms as well as address our most frequent support requests. Developers using our math libraries currently will find the new release build-compatible with the prior release. Upgrades are provided free o...
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Non-linear Curve Fitting

Posted on by Paul Shirkey
SIGA, a public biotechnology company, recently hired CenterSpace consultants to refine their logistic modeling capabilities. Modeling a dose-response system with a logistic curve is one important special case of the more general non-linear curve fitting problem. If you are familiar with linear regression and related statistics, the non-linear case closely parallels the linear case making the jump ...
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Probability Distributions in NMath Stats

Posted on by Paul Shirkey
Probability distributions are central to many applications in statistical analysis. The NMath Stats library offers a large set of probability distributions, covering most domains of application, all with an easy to use common interface. Each distribution class uses numerically stable accurate algorithms to compute both the probability distribution and the cumulative distribution. In this post we...
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Drawing Dendrograms

Posted on by Ken Baldwin
A dendrogram is a tree diagram often used to visualize the results of hierarchical clustering. A customer recently contacted us asking for help drawing dendrograms from the output of the hierarchical clustering algorithm in NMath Stats. See here. UserZoom is an international software company specializing in web customer experience and usability testing. UserZoom software includes a tool to run o...
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Cluster Analysis, Part V: Monte Carlo NMF

Posted on by Ken Baldwin
In this continuing series, we explore the NMath Stats functions for performing cluster analysis. (For previous posts, see Part 1 - PCA , Part 2 - K-Means, Part 3 - Hierarchical, and Part 4 - NMF.) The sample data set we're using classifies 89 single malt scotch whiskies on a five-point scale (0-4) for 12 flavor characteristics. To visualize the data set and clusterings, we make use of the free Mic...
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