R4SPISE2022 provide data, programs, and documentation for the SPISE-2022 Advanced Workshop on Sensory Evaluation (July 27, 2022 to July 28, 2022; to take place in Hanoi Vietnam).
Installation
You can install the development version of R4SPISE2022 with the following lines of code:
# if remotes is not installed, decomment the following line
# install.packages('remotes')
remotes::install_github('HerveAbdi/R4SPISE2022')To install the vignettes while installing the package, then run the following commands:
remotes::install_github('HerveAbdi/R4SPISE2022',
build_vignettes = TRUE,
force = TRUE)Example
This is a basic example which shows how to solve a common problem:
library(R4SPISE2022)
## load data
data("sixBeers12Descriptors10Judges", package = "data4PCCAR")
beers <- sixBeers12Descriptors10Judges$ratingsIntensity
## run PCA
res.pca <- epPCA(beers,
center = TRUE, # Center the data
scale = FALSE, # **Do not** scale the variables
graphs = FALSE)
## generate plots for descriptive results
res.plot.pca <- OTAplot(resPCA = res.pca,
data = beers)
## generate plots for inference results
res.plot.pca.inference <- OTAplotInference(resPCA = res.pca,
data = beers)List of main functions
OTAplot(): Core function to generate figures for descriptive results from one table analysis (i.e., principal component analysis; PCA)OTAplotInference(): Core function to generate figures for inference results from one table analysis (i.e., PCA)TTAplot(): Core function to generate figures for descriptive results from two table analyses (i.e., PLSC, CCA, and RA)TTAplotInferenct(): Core function to generate figures for inference results from two table analyses (only PLSC for now)PLSRplot(): Core function to generate figures for descriptive and inference results from partial least square regression (PLSR)