GraphiXT 1.21.4.4

GraphiXT is a data analysis software and numerical computing environment. The original purpose of GraphiXT was to facilitate study of time dependences of a large number of interdependent quantities. Consequently, graphs displayed by GraphiXT are of two types: graphs of functions f(t), whose argument is time, and graphs of functions f(x,t), whose arguments are coordinate and time. However, the actual meaning of arguments is up to the user. ...

Author Vilnius University, Faculty of Physics
License Freeware
Price FREE
Released 2015-09-14
Downloads 103
Filesize 10.05 MB
Requirements Windows XP SP2 or a newer version of Windows
Installation Install and Uninstall
Keywords Nonlinear fitting, computational programming, 1D charge transport simulation
Users' rating
(4 rating)
GraphiXTScienceWin2000, Windows XP, Windows 7 x32, Windows 7 x64, Windows 8, Windows 10, WinServer, WinOther, Windows Vista, Windows Vista x64
GraphiXT statistical software - Download Notice

Using GraphiXT Free Download crack, warez, password, serial numbers, torrent, keygen, registration codes, key generators is illegal and your business could subject you to lawsuits and leave your operating systems without patches. We do not host any torrent files or links of GraphiXT on rapidshare.com, depositfiles.com, megaupload.com etc. All GraphiXT download links are direct GraphiXT full download from publisher site or their selected mirrors.
Avoid: statistical software oem software, old version, warez, serial, torrent, GraphiXT keygen, crack.
Consider: GraphiXT full version, statistical software full download, premium download, licensed copy.

GraphiXT statistical software - The Latest User Reviews

Most popular Science downloads

GraphiXT

1.21.4.4 download

GraphiXT is a data analysis software and numerical computing environment. The original purpose of ... others, - elementary data analysis: linear fitting, integration, statistical analysis, - nonlinear least-squares fitting and solution of ...

KNN-WG

1.0 download

... This method has its origin as a non-parametric statistical pattern recognition procedure to distinguish between different patterns according to a selection criterion. Through this method, researchers can generate future data. ...