plot_param_evolution: Plot the evolution of different fitting parameters across all...

In santaR: Short Asynchronous Time-Series Analysis

Plot the evolution of different fitting parameters across all possible df for each eigenSpline

Description

Plot the evolution of 5 different fitting metrics (CV: Cross-Validation, GCV: Generalised Cross-Validation, AIC: Akaike Information Criterion, BIC: Bayesian Information Criterion, AICc: Akaike Information Criterion Corrected for small sample size) over all possible df for each eigenSpline generated by get_param_evolution.

Usage

plot_param_evolution(paramSpace, scaled = FALSE)

Arguments

paramSpace	A list of n matrices (n being the number or eigenSplines) as generated by plot_param_evolution. Each matrix of fitting parameters has as rows different fitting metrics, as columns different df values.
scaled	(bool) If TRUE, the value of each eigenSpline fitting parameter are scaled between 0 and 1. Default is TRUE.

Value

A list of ggplot2 plotObjects, one plot per fitting parameters. All results can be plotted using do.call(grid.arrange, returnedResult)

See Also

Graphical implementation with santaR_start_GUI

Other DFsearch: get_eigen_DFoverlay_list(), get_eigen_DF(), get_eigen_spline(), get_param_evolution(), plot_nbTP_histogram()

Examples

## 8 subjects, 4 time-points, 3 variables
inputData  <- acuteInflammation$data[0:32,1:3]
ind        <- acuteInflammation$meta$ind[0:32]
time       <- acuteInflammation$meta$time[0:32]
eigen      <- get_eigen_spline(inputData, ind, time, nPC=NA, scaling="scaling_UV",
                               method="nipals", verbose=TRUE, centering=TRUE, ncores=0)
paramSpace <- get_param_evolution(eigen, step=0.25)
plotList   <- plot_param_evolution(paramSpace, scaled=TRUE)
plotList[1]
#do.call(grid.arrange, plotList )

santaR documentation built on May 24, 2022, 1:06 a.m.