STATISTICA

Since 1984, StatSoft has been developing the STATISTICA suite of analytics software products and solutions. STATISTICA provides the most comprehensive array of data analysis, data management, data visualization, and data mining solutions. Techniques include the widest selection of predictive modeling, clustering, classification, and exploratory techniques in one software platform. STATISTICA is a tried and true analytics platform with more than two decades of history in delivering successful business results for our customers, a global user base of more than 1 million users.

This software is also referenced in ORMS.


References in zbMATH (referenced in 37 articles )

Showing results 21 to 37 of 37.
Sorted by year (citations)
  1. Marrero-Ponce, Yovani; Castillo-Garit, Juan Alberto; Castro, Eduardo A.; Torrens, Francisco; Rotondo, Richard: 3D-chiral (2.5) atom-based TOMOCOMD-CARDD descriptors: theory and QSAR applications to central chirality codification (2008)
  2. Munteanu, Cristian Robert; González-Díaz, Humberto; Borges, Fernanda; de Magalhães, Alexandre Lopes: Natural/random protein classification models based on star network topological indices (2008)
  3. Munteanu, Cristian Robert; González-Díaz, Humberto; Magalhães, Alexandre L.: Enzymes/non-enzymes classification model complexity based on composition, sequence, 3D and topological indices (2008)
  4. Marques de Sá, Joaquim P.: Applied statistics. Using SPSS, STATISTICA, MATLAB and R. With CD-ROM. (2007)
  5. Weiß, Christian H.: Statsoft, Inc., Tulsa, OK.: STATISTICA, version 8 (2007)
  6. Cruz-Monteagudo, Maykel; González-Díaz, Humberto; Borges, Fernanda; González-Díaz, Yenny: Simple stochastic fingerprints towards mathematical modeling in biology and medicine. III: Ocular irritability classification model (2006)
  7. Pérez González, Maykel; Caballero, Julio; Morales Helguera, Aliuska; Garriga, Miguel; González, Gerardo; Fernández, Michael: 2D autocorrelation modelling of the inhibitory activity of cytokinin-derived cyclin-dependent kinase inhibitors (2006)
  8. Borg, Ingwer; Groenen, Patrick J. F.: Modern multidimensional scaling. Theory and applications. (2005)
  9. Afifi, Abdelmonem; Clark, Virginia A.; May, Susanne: Computer-aided multivariate analysis. (2004)
  10. Kiełtyka, Leszek; Kucȩba, Robert; Sokołowski, Adam: Application of neural network topologies in the intelligent heat use prediction system (2004)
  11. Hitzl, W.; Reitsamer, H. A.; Hornykewycz, K.; Mistlberger, A.; Grabner, G.: Application of discriminant, classification tree and neural network analysis to differentiate between potential glaucoma suspects with and without visual field defects (2003)
  12. Marques de Sá, J. P.: Applied statistics using SPSS, STATISTICA and MATLAB. (With CD-ROM) (2003)
  13. Dzemyda, Gintautas: Visualization of a set of parameters characterized by their correlation matrix. (2001)
  14. Funtova, V.; Malyshev, L.: Differentiation of populations of Agrostis tenuis Sibth. and Dactylis glomerata L. in the flood meadow habitats of the Luga river (2001)
  15. Vadzinskij, R. N.: Handbook of probability distributions. (2001)
  16. Afifi, A. A.; Clark, V.: Computer-aided multivariate analysis. (1996)
  17. Wilhelm, Adalbert: Software review. Statistica 4. 3 for Windows (1994)

Further publications can be found at: http://www.statsoft.com/Resources/Library/Literature