Partial least-squares regression on design variables as an alternative to analysis of variance
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Optimising drone flight planning for measuring horticultural tree crop structure
2020, ISPRS Journal of Photogrammetry and Remote SensingCitation Excerpt :Also, there was multi-collinearity between some variables, e.g. between the average pitch angle and flying speed, and between pixel GSD, average image area, and image forward overlap. PLS is better equipped to analyse variables with multi-collinearity by projecting both the independent and dependent datasets to principal component spaces, while still maximising the covariance between independent and dependant datasets at the same time (Martens et al., 1986; Wold et al., 1984). We used both the original five-variable set (variable set 1) and the extended eight-variable set (variable set 2) to run the PLS regression against each quality indicator individually (Table 2) and generated a prediction model for each variable set.
Analysis of designed experiments by stabilised PLS regression and jack-knifing
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2001, Food Quality and PreferencePARAFAC. Tutorial and applications
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Present address: Norwegian Computing Center, Blindern, Oslo 3 (Norway).
- 2
Present address: Instituto Agroquimica y Tecnologia de Alimentos, 46010 Valencia (Spain).