Data Analysis & Simulation

Archive for the ‘EasyFitXL’ Category


EasyFitXL Is Now Compatible With Excel 2010

Monday, July 12th, 2010

EasyFitXL - the distribution fitting add-in for Excel - was first introduced with the release of EasyFit 4.0 back in 2007. When designing EasyFitXL, we did a lot of research as to which Excel versions to support. At that time, the latest version of Excel was Excel 2007, which included some new useful features, such as the support for larger worksheets and multi-threaded worksheet recalculation capability. However, many customers were not rushing to upgrade to Excel 2007 because of it’s controversial Ribbon Interface, so we had to make EasyFitXL compatible with the previous version - Excel 2003.

According to some publicly available data, Excel 2002 and Excel 2000 still had a considerable user base, so we have made a decision to support these two older versions as well. As a result, EasyFitXL initially included support for Excel versions from 2000 through 2007, covering perhaps over 99% of all Excel installations in the world.

Last month Microsoft has released Excel 2010 which does not make a big difference in terms of data analysis, however, with its release we started receiving compatibility complaints from our customers, so we performed an in-depth testing and released an updated version of EasyFit (available for download).

EasyFit 5.3 Released

Wednesday, January 20th, 2010

Recently a customer has contacted us and noted that the Inverse Cumulative Distribution Function (the Quantile Function) of the Inverse Gaussian distribution implemented in EasyFit works well for lambda=1902.1, mu=41857.0 and P=0.9, but fails for the same lambda & mu and P=0.99. Last week we have released an updated version of EasyFit that fixes the problem, and in this post we would like to elaborate more on the issue.

Evaluating the Inverse CDF of the Inverse Gaussian Model
Since the CDF of the Inverse Gaussian distribution is quite complicated (expressed in terms of the two Laplace Integrals), the Inverse CDF of this model is not available in closed form, and cannot be easily evaluated for a given set of distribution parameters. Initially, we have implemented an iterative approximation algorithm that evaluates the ICDF(P) using the CDF as well as the PDF to speed up the calculation. The algorithm itself works very well over a great range of input parameters, however, we have placed a limitation on how many iterations it is allowed to perform.

Because EasyFit is considered an interactive data analysis tool, we are always looking for a balance between the feature set and the performance, which is especially important when using EasyFit with Excel worksheets calculated in real time. The limitation on the number of iterations is necessary to make sure the algorithm doesn’t fall into an “infinite loop”, meaning the situation when it’s unable to reach the specified accuracy regardless of how long it continues to work. The problem usually happens when we are hitting the precision limitations of the computer’s CPU: in theory, the algorithm must converge in a limited number of steps, but in reality, it will just continue iterating over and over again without any accuracy improvements.

As a solution, we have made some improvements to the algorithm, making it more robust and efficient, so it now works with the same accuracy, but for a larger range of input parameters. For example, considering the parameters that initially caused the problem (lambda=1902.1 and mu=41857.0), the ICDF(P) can be evaluated for values of P up to 0.999925, which is more than enough for most statistical analysis applications.

Should You Upgrade?
Since this minor issue does not affect the accuracy of distribution fitting, you only need to upgrade if you are experiencing problems evaluating the Inverse CDF of the Inverse Gaussian distribution for P>0.9, otherwise EasyFit 5.2 will still work well for you.

Using Distribution Functions in Excel Sheets

Tuesday, January 13th, 2009

There are many probability distributions developed by statisticians to model random data of different kinds, ranging from business data, finance data (stock prices) to engineering data (system failures) and environmental data (max. flood flows). While the standard Excel package includes some basic statistical functions, its support for probability distributions is very limited and almost useless for real world modelling applications. This article discusses the worksheet functions provided by EasyFitXL, the distribution fitting add-in for Excel that can be applied to perform a range of decision-making calculations using a variety of probability distributions… read the full article

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