论文信息 - The geometry of ASCA

The geometry of ASCA

For analyzing designed high‐dimensional data, no standard methods are currently available. A method that is becoming more and more popular for analyzing such data is ASCA. The mathematics of ASCA are already described elsewhere but a geometrical interpretation is still lacking. The geometry can help practitioners to understand what ASCA does and the more advanced user can get insight into the properties of the method. This paper shows the geometry of ASCA in both the row‐ and column‐space of the matrices involved. Copyright © 2008 John Wiley & Sons, Ltd.

[1] Thomas Hankemeier,et al. Effects of growth conditions and processing on Rehmannia glutinosa using fingerprint strategy. , 2006, Planta medica.

[2] Age K. Smilde,et al. Discovering gene expression patterns in time course microarray experiments by ANOVA-SCA , 2007, Bioinform..

[3] Peter de B. Harrington,et al. Analysis of variance–principal component analysis: A soft tool for proteomic discovery , 2005 .

[4] Marieke E. Timmerman,et al. Four simultaneous component models for the analysis of multivariate time series from more than one subject to model intraindividual and interindividual differences , 2003 .

[5] Svante Wold,et al. Multivariate analysis of variance (MANOVA) , 1990 .

[6] J. J. Jansen,et al. ASCA: analysis of multivariate data obtained from an experimental design , 2005 .

[7] Rasmus Bro,et al. Multi-way Analysis with Applications in the Chemical Sciences , 2004 .

[8] Age K. Smilde,et al. ANOVA-simultaneous component analysis (ASCA): a new tool for analyzing designed metabolomics data , 2005, Bioinform..

[9] Age K. Smilde,et al. Statistical validation of megavariate effects in ASCA , 2007, BMC Bioinformatics.