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4_ModelStatComparisons.R
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4_ModelStatComparisons.R
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library(dplyr)
library(ggplot2)
library(ggtext)
library(ggpubr)
#setwd("YOUR_DIRECTORY")
# Read in data
glm2D <- read.csv("Appendix Material/GLM2DModelDiagnosticStats.csv")
glm3D <- read.csv("Appendix Material/GLM3DModelDiagnosticStats.csv")
ogNames <- names(glm3D)
glmDiff <- glm3D[,-1] - glm2D[,-1]
names(glm2D)[-1] <- paste0(names(glm2D)[-1], "_2D")
names(glm3D)[-1] <- paste0(names(glm3D)[-1], "_3D")
names(glmDiff) <- paste0(names(glmDiff), "_3D-2D")
glmDiff$species <- glm2D$species
# Look at relevant correlations
pearCor <- cor(glm2D[,5:10], glm3D[,5:10],
use = "pairwise.complete.obs")
write.csv(pearCor, "Appendix Material/CorrelationAmongModelStats.csv")
allGLMStats <- merge(glm2D, glm3D)
allGLMStats <- merge(allGLMStats, glmDiff)
# Statistical tests
wilcox.test(allGLMStats$nPres_2D, allGLMStats$nPres_3D,
paired=TRUE, alternative = "less")
wilcox.test(allGLMStats$nAbs_2D, allGLMStats$nAbs_3D,
paired=TRUE, alternative = "less")
wilcox.test(allGLMStats$AUC_2D, allGLMStats$AUC_3D,
paired=TRUE, alternative = "less")
wilcox.test(allGLMStats$AIC_2D, allGLMStats$AIC_3D,
paired=TRUE, alternative = "less")
wilcox.test(allGLMStats$Kappa_2D, allGLMStats$Kappa_3D,
paired=TRUE, alternative = "greater")
wilcox.test(allGLMStats$TSS_2D, allGLMStats$TSS_3D,
paired=TRUE, alternative = "greater")
write.csv(allGLMStats, "Appendix Material/AllModelStatistics.csv", row.names = FALSE)
AUCplot <- ggplot(allGLMStats, aes(x = AUC_2D, y = AUC_3D)) +
geom_point() +
scale_color_gradient() +
geom_abline(slope = 1, intercept = 0) +
geom_smooth(method='lm', col = "red") +
labs(x = "2D Model AUC", y = "3D Model 3D") +
theme_classic() +
theme(legend.position = "none")
AICplot <- ggplot(allGLMStats, aes(x = AIC_2D, y = AIC_3D)) +
geom_point() +
scale_color_gradient() +
geom_abline(intercept = 0, slope = 1) +
geom_smooth(method='lm', col = "red") +
labs(x = "2D Model AIC", y = "3D Model AIC") +
theme_classic() +
theme(legend.position = "none")
TSSplot <- ggplot(allGLMStats, aes(x =TSS_2D, y = TSS_3D)) +
geom_point() +
scale_color_gradient() +
geom_abline(intercept = 0, slope = 1) +
geom_smooth(method='lm', col = "red") +
labs(x = "2D Model TSS",
y = "3D Model TSS") +
theme_classic() +
theme(legend.position = "none")
KappaPlot <- ggplot(allGLMStats, aes(x =Kappa_2D, y = Kappa_3D)) +
geom_point() +
scale_color_gradient() +
geom_abline(intercept = 0, slope = 1) +
geom_smooth(method='lm', col = "red") +
labs(x = "2D Model Kappa",
y = "3D Model Kappa") +
theme_classic() +
theme(legend.position = "none")
# Plot 'em
pdf("Appendix Material/ModelStatPlots.pdf")
ggarrange(AUCplot, AICplot,
TSSplot, KappaPlot,
ncol = 2, nrow = 2)
dev.off()
# For overplotting
names(glm2D) <- ogNames
names(glm3D) <- ogNames
glm2D$modelDim <- "2D"
glm3D$modelDim <- "3D"
allGLMStatsLong <- rbind(glm2D,glm3D)
AUCpres <- ggplot(allGLMStatsLong, aes(x = nPres, y = AUC, col = modelDim)) +
geom_point() +
geom_smooth(method='lm') +
labs(x = "Number of Presences") +
theme_classic() +
theme(legend.position = "none")
AICpres <- ggplot(allGLMStatsLong, aes(x = nPres, y = AIC, col = modelDim)) +
geom_point() +
geom_smooth(method='lm') +
labs(x = "Number of Presences") +
theme_classic() +
theme(legend.position = "none")
TSSpres <- ggplot(allGLMStatsLong, aes(x = nPres, y = TSS, col = modelDim)) +
geom_point() +
geom_smooth(method='lm') +
labs(x = "Number of Presences") +
theme_classic() +
theme(legend.position = "none")
KappaPres <- ggplot(allGLMStatsLong, aes(x = nPres, y = Kappa, col = modelDim)) +
geom_point() +
geom_smooth(method='lm') +
labs(x = "Number of Presences") +
theme_classic() +
theme(legend.position = "none")
legendPlot <- ggplot(allGLMStatsLong, aes(x = AUC, y = AUC,
col = modelDim))+
geom_point()+
lims(x = c(0,0), y = c(0,0))+
theme_void()+
labs(col="Model\nDimensions")+
theme(legend.position = c(0.5,0.5),
legend.key.size = unit(1, "cm"),
legend.text = element_text(size = 12),
legend.title = element_text(size = 15, face = "bold"))+
guides(colour = guide_legend(override.aes = list(size=8)))
# Plot 'em
pdf("Appendix Material/ModelStatPlotsVsPresences.pdf")
ggarrange(AUCpres, AICpres,
TSSpres, KappaPres, legendPlot,
ncol = 3, nrow = 2)
dev.off()