Compositional Data Linear Models with Composition Redistribution
Add ILR coordinates to a data.frame containing composition variables
Sanity checks for arguments passed to predict_delta_comps()
Check if compositional variable are strictly greater than 0
Check whether columns exist in a data.frame
Statistical test of the collective significance of the ilr variables
Creates row-wise perturbations of compositions from the mean compositi...
Create ilr basis matrix (V)
Extract critical quantities from a lm object (for confidence interval ...
fit linear model based on input data.frame
Is object that is returned from pred_delta_comps()?
Is object that is returned from lm()?
Catch NULL, empty and objects containing NAs
Plot redistributed time-use predictions from compositional ilr multipl...
Get predictions from compositional ilr multiple linear regression mode...
Print the ilr transformation of provided composition parts to console
Provided data containing an outcome variable, compositional variables and additional covariates (optional); linearly regress the outcome variable on an isometric log ratio (ilr) transformation of the linearly dependent compositional variables. The package provides predictions (with confidence intervals) in the change (delta) in the outcome/response variable based on the multiple linear regression model and evenly spaced reallocations of the compositional values. The compositional data analysis approach implemented is outlined in Dumuid et al. (2017a) <doi:10.1177/0962280217710835> and Dumuid et al. (2017b) <doi:10.1177/0962280217737805>.