partial least square (pls) regression and correlation analyses  (Addinsoft inc)

Journal: Ambio

Article Title: Land use influences macroinvertebrate community composition in boreal headwaters through altered stream conditions

doi: 10.1007/s13280-016-0837-y

Figure Lengend Snippet: Results from partial least squares regression (PLS) analyses of catchment-scale characteristics as predictors of in-stream or macroinvertebrate variables. Numbers represent loadings (including direction of relationship) of predictor variables that obtained a VIP > 1.0 and cumulative amount of response variable variation explained by the first (C1) and second (C2) model component. SWD small woody debris, DOC dissolved organic carbon, SRP soluble reactive phosphorus, AFDM ash-free dry mass, PC principal component

Article Snippet: PLS regression analyses were performed using XLSAT (XLSTAT 2015.2.01, Addinsoft SRAL, Germany), and CCA were performed using the vegan library (Oksanen et al. ) in R (R Core Team ).

Techniques:

Journal: Ambio

Article Title: Land use influences macroinvertebrate community composition in boreal headwaters through altered stream conditions

doi: 10.1007/s13280-016-0837-y

Figure Lengend Snippet: Results from partial least squares regression (PLS) analyses of in-stream environmental conditions as predictors of macroinvertebrate variables. Numbers represent loadings (including direction of relationship) of predictor variables that obtained a VIP > 1.0 and cumulative amount of response variable variation explained by the first (C1) and second (C2) model component. SWD small woody debris, DOC dissolved organic carbon, SRP soluble reactive phosphorus, AFDM ash-free dry mass, PC principal component

Article Snippet: PLS regression analyses were performed using XLSAT (XLSTAT 2015.2.01, Addinsoft SRAL, Germany), and CCA were performed using the vegan library (Oksanen et al. ) in R (R Core Team ).

Techniques:

Journal: Sensors (Basel, Switzerland)

Article Title: Estimation of Biomass and Canopy Height in Bermudagrass, Alfalfa, and Wheat Using Ultrasonic, Laser, and Spectral Sensors

doi: 10.3390/s150202920

Figure Lengend Snippet: Explanation of variation in dependent variable (VDV) from partial least squares regression modeling for dry biomass and canopy height by sensor estimation models and model equations for height (combination ultrasonic and laser model) and biomass (two sensor model: laser and ultrasonic combination, and three sensor model: laser, ultrasonic and NDVI combination). † MIX-Mixture of alfalfa and bermudagrass; ‡ ALL-All monoculture and mixed species from the alfalfa and bermudagrass experiment.

Article Snippet: Estimation models were constructed using partial least squares (PLS) regression analyses (SAS PROC PLS) with CVTEST for selection of simplest models [ – ].

Techniques:

Journal: PLoS Neglected Tropical Diseases

Article Title: A Colour Opponent Model That Explains Tsetse Fly Attraction to Visual Baits and Can Be Used to Investigate More Efficacious Bait Materials

doi: 10.1371/journal.pntd.0003360

Figure Lengend Snippet: Multivariate partial least squares regression analysis of log transformed tsetse fly catches using calculated photoreceptor excitations as predictors.

Article Snippet: PLS regression analyses were conducted using Minitab 14.20 (Minitab Inc., State College PA, USA); all other statistical analyses were conducted using SPSS version 19.0 (IBM Corp., Armonk NY, USA).

Techniques: Transformation Assay