ANOVA–simultaneous component analysis

From GM-RKB
(Redirected from ASCA)
Jump to navigation Jump to search

A ANOVA–simultaneous component analysis is a multivariate extension of ANOVA algorithm.



References

2016

  • (Wikipedia, 2016) ⇒ https://www.wikiwand.com/en/ANOVA%E2%80%93simultaneous_component_analysis Retrieved 2016-07-31
    • Analysis of variance – simultaneous component analysis (ASCA or ANOVA–SCA) is a method that partitions variation and enables interpretation of these partitions by SCA, a method that is similar to principal components analysis (PCA). This method is a multivariate or even megavariate extension of analysis of variance (ANOVA). The variation partitioning is similar to ANOVA. Each partition matches all variation induced by an effect or factor, usually a treatment regime or experimental condition. The calculated effect partitions are called effect estimates. Because even the effect estimates are multivariate, interpretation of these effects estimates is not intuitive. By applying SCA on the effect estimates one gets a simple interpretable result. In case of more than one effect this method estimates the effects in such a way that the different effects are not correlated.

2005