At last, it takes 6 logistics parks as an example to investigate the evaluation system based on statistical analysis software SPSS and main component analysis.
A factor analysis for all items of the ECQ was conducted using main component analysis with varimax rotation.
This new analysis also produced a new panel in Figure 2. The main Principal Component Analysis (PCA) is now verified using two different non-linear factorization techniques: Isomapping and Local Linear Embedding.
Prior to conducting the main exploratory factor analyses (EFA) an unforced principal components analysis (PCA) was run.
Principal components analysis was applied to synthesize their main peat properties and underlying processes.
Global main effects principal component analysis was performed as previously described (Box et al., 2005).
Figure 1 figure supplement 1 provides a global main effects principal component analysis for all GF and SM used in this second screen.
Consistent with this observation, a global main effects principal component analysis of all GF and SM revealed that CHR, WNT, Rspondin and FGF exerted the most potent effects on GFP expression.
DOI: http://dx.doi.org/10.7554/eLife.08413.003 10.7554/eLiFigure1 figureigure 1—figure supplement 1. Global main effects principal component analysis of GF and SM ACME screen demonstrates that WNT and FGF agonists exert positive effects on T-GFP expression.
The b i -axis may be interpreted in the sense of main axis from principal component analysis.
