plotAIC: Plots the AIC across model specifications.

In speccurvieR: Easy, Fast, and Pretty Specification Curve Analysis

Plots the AIC across model specifications.

Description

plotAIC() plots the Akaike information criterion across model specifications. Only available for nonlinear regression models.

Usage

plotAIC(sca_data, title = "", showIndex = TRUE, plotVars = TRUE)

Arguments

sca_data	A data frame returned by 'sca()' containing model estimates from the specification curve analysis.
title	A string to use as the plot title. Defaults to an empty string, '""'.
showIndex	A boolean indicating whether to label the model index on the the x-axis. Defaults to 'TRUE'.
plotVars	A boolean indicating whether to include a panel on the plot showing which variables are present in each model. Defaults to 'TRUE'.

Value

If 'plotVars = TRUE' returns a grid grob (i.e. the output of a call to 'grid.draw'). If 'plotVars = FALSE' returns a ggplot object.

Examples

plotAIC(sca_data = sca(y = "Salnty", x = "T_degC",
                       controls = c("ChlorA", "O2Sat"),
                       data = bottles, progressBar = TRUE, parallel = FALSE),
                     title = "AIC");
plotAIC(sca_data = sca(y = "Salnty", x = "T_degC",
                       controls = c("ChlorA*O2Sat"),
                       data = bottles, progressBar = FALSE,
                       parallel = FALSE),
                       showIndex = FALSE, plotVars = FALSE);
plotAIC(sca_data = sca(y = "Salnty", x = "T_degC",
                         controls = c("ChlorA*NO3uM", "O2Sat*NO3uM"),
                         data = bottles,
                         progressBar = TRUE, parallel = TRUE, workers = 2));

speccurvieR documentation built on Oct. 10, 2024, 1:08 a.m.