Modeling a dose-response system with a logistic curve is one important special case of the more general non-linear curve fitting problem. The logistic model is a fundamental non-linear model for many systems, and is widely used in the life sciences, medicine, and environmental toxicology. In a previous blog post, Ken outlined the techniques for using NMath for computing various common linear trend lines and non-linear trend lines linearizable via a simple variable substitution. This post extends that curve fitting article to the non-linear case using the logistic as the running example.

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All of us at CenterSpace software are proud to announce a partnership with Nevron, leaders in data visualization. Nevron builds .NET components which enable developers to quickly build clean, enterprise quality, user interfaces incorporating well rendered maps, gauges, diagrams, or charts. Check out our partnership page for more information and free examples.

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We are sometimes asked how to reproduce the various Excel Trendline types in NMath: Linear, Logarithmic, Exponential, Power, Polynomial, and Moving Average. In this post, we show you how to compute each trendline using NMath, including printing out the form of the equation and the R2 value (coefficient of determination). 

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Version 4.0 of the .NET Framework introduced a new runtime activation policy, which enables an application to activate multiple versions of the common language runtime (CLR) in the same process. (See here for more information.)
Because of this support for side-by-side runtimes, .NET 4.0 has changed the way that it binds to older mixed-mode assemblies,…

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Multiple Linear Regression (MLR) is a powerful approach to modeling the relationship between one or two or more explanatory variables and a response variable by fitting a linear equation to observed data. This is the second part in a three part series on PCR.

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