Table 1.
Entry | Unit | Range | Num. LV[a] | Variance captured [%] | RMSEC[b] | RMSECV | RE[c] [%] | R 2 Cal. | R 2 CV[d] | |
---|---|---|---|---|---|---|---|---|---|---|
X (FTIR) | Y (Cal.) | |||||||||
1 | M n | 4626 | 7 | 94 | 94 | 260 | 400 | 8.7 | 0.94 | 0.85 |
2 | log(M n) | 0.95 | 7 | 94 | 98 | 0.034 | 0.059 | 6.2 | 0.98 | 0.94 |
3 | M w | 29 984 | 10 | 96 | 92 | 1500 | 3000 | 10 | 0.92 | 0.70 |
4 | log(M w) | 1.7 | 6 | 93 | 94 | 0.091 | 0.13 | 7.6 | 0.94 | 0.88 |
5 | D | 5.03 | 5 | 89 | 72 | 0.69 | 1.0 | 20 | 0.72 | 0.44 |
6 | β‐O‐4 | 34 | 4 | 85 | 94 | 1.8 | 2.8 | 8.2 | 0.94 | 0.85 |
7 | β‐5 | 10 | 4 | 86 | 88 | 0.74 | 1.1 | 11 | 0.88 | 0.75 |
8 | β‐β | 3.9 | 5 | 90 | 85 | 0.33 | 0.53 | 14 | 0.85 | 0.61 |
[a] Num. LV=number of latent variables. [b] RMSEC=root mean squared error of calibration. [c] RE=RMSECV/range. [d] Venetian blinds with 10 splits and 1 sample per split; values reported to 2 significant figures; see Figure S2 for the associated regression vectors.