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Aura

Auraź Is the automated expert system for multivariate statistical forecasting. It combines the unique power of full automated multivariate statistical analysis in unlimited dimensions with the remarkable ease of use. Be you the experienced mathematician or just a novice in forecasting with immediate and very practical goals, Auraź is just for you. It can both offer the instant forecast by one mouse click or expand for you many levels of complicated model trees that stay behind a few final digits. You can watch accurate and attractive charts, detailed tables and very sophisticated multilevel model descriptions linked with intuitive hypertext links designed not to get you lost in this abundance of models. You can instantly import tremendous amounts of data both from the desktop applications and external databases, analyze them with one mouse click and store to disk with unique speed in native format as well as export results for the further use in many formats. If you are software developer not interested in these visual features, then even more you can benefit from Auraź power and flexibility, because it offers you many levels of simple and effective open user APIs to access custom data sources, incorporate additional forecasting models, store results in the external databases of your choice or just embed the whole engine into your custom application and enjoy all its power through the customized web interface which best fits your needs. Aura is licensed as shareware, the cost of the registered verison is $500 and full size of the download is 5.89 MB. You may download a free version of Aura by following download link at Free Download section of this page. Aura is developed or distributed by Econom-Expert Ltd. and is listed under finance stock management.

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Expert system for adaptive automated forecasting of financial markets

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 Download URL: Download Now!
 Publisher: Econom-Expert Ltd.
 Cost: $500
 License Type: Shareware
 File Size: 5.89 MB
 Release Date: 11/7/2003
 Platform: Win98,WinME,WinNT 4.x,WinXP,Windows2000
 Keywords: forecasting prediction time series

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