SIMCA
SIMCA: The Standard in Multivariate Data Analysis. For over three decades, Sartorius Stedim Data Analytics AB has helped engineers, analysts and scientists master their data using SIMCA. Whether it is large amounts of data, batch data, time-series data or other data, SIMCA transforms your data into visual information for easy interpretation. This enables you to make decisions and take action – quickly and with confidence. And SIMCA will continue to meet your data analysis needs, now and in the future.
Keywords for this software
References in zbMATH (referenced in 5 articles )
Showing results 1 to 5 of 5.
Sorted by year (- Magnanensi, Jérémy; Bertrand, Frédéric; Maumy-Bertrand, Myriam; Meyer, Nicolas: A new universal resample-stable bootstrap-based stopping criterion for PLS component construction (2017)
- Julie Josse; François Husson: missMDA: A Package for Handling Missing Values in Multivariate Data Analysis (2016) not zbMATH
- Winberg, T. Mikael; Hellgren, Jenny M.; Palm, Torulf: Stimulating positive emotional experiences in mathematics learning: influence of situational and personal factors (2014) MathEduc
- Denimal, Jean-Jacques: Optimized hierarchical factorial classification of a data table (2007)
- Vinzi, Vincenzo Esposito; Guinot, Christiane; Squillacciotti, Silvia: Two-step PLS regression for L-structured data: an application in the cosmetic industry (2007)