This version of R package “**mod**el **Ev**aluation and **A**nalysis” includes some **bug fixes** (thanks to Huijie Qiao, Ying-Ju Tessa Chen, Oswald van Ginkel and Alba Estrada), some **new functions** (*predPlot*, *confusionLabel*, and *mod2obspred*, which is now used internally by several others), and it implements more classes (‘gam’, ‘gbm’, ‘randomForest’, ‘bart’) besides ‘glm’ for the ‘`model`

‘ argument in most functions. There are also a few **argument additions and improvements** — e.g.,* varPart *now has an option to plot the circles in colour (thanks to Oswald van Ginkel). You can read the package NEWS file for details.

You can now **install the newest version of modEvA from CRAN** and try out some of these new features:

`install.packages("modEvA")`

`library(modEvA)`

**# load some other packages to make different models:**`library(gam)`

library(gbm)**# take a sample dataset and create a numeric binary response variable:**`data(kyphosis)`

head(kyphosis)

kyphosis$Kyphosis <- ifelse(kyphosis$Kyphosis == "present", 1, 0)

**# make different models with this response variable:**`mod_glm <- glm(Kyphosis ~ Age + Number + Start, family = binomial, data = kyphosis)`

mod_gam <- gam(Kyphosis ~ s(Age) + s(Number) + s(Start), family = binomial, data = kyphosis)

mod_gbm <- gbm(Kyphosis ~ Age + Number + Start, distribution = "bernoulli", data = kyphosis)

**# get different evaluation metrics/plots directly from the model objects:****# e.g., density of predictions for presences and absences:**`predPlot(model = mod_glm, main = "GLM")`

predPlot(model = mod_gam, main = "GAM")

predPlot(model = mod_gbm, main = "GBM")

predDensity(model = mod_glm, main = "GLM")

predDensity(model = mod_gam, main = "GAM")

predDensity(model = mod_gbm, main = "GBM")

# # (area under the) ROC and Precision-Recall curves:

`AUC(model = mod_glm, main = "GLM")`

AUC(model = mod_gam, main = "GAM")

AUC(model = mod_gbm, main = "GBM")

AUC(model = mod_glm, curve = "PR", main = "GLM")

AUC(model = mod_gam, curve = "PR", main = "GAM")

AUC(model = mod_gbm, curve = "PR", main = "GBM")

AUC(model = mod_gam, main = "GAM")

AUC(model = mod_gbm, main = "GBM")

AUC(model = mod_glm, curve = "PR", main = "GLM")

AUC(model = mod_gam, curve = "PR", main = "GAM")

AUC(model = mod_gbm, curve = "PR", main = "GBM")

You can try also other functions such as ‘

‘, ‘**threshMeasures**

‘ or ‘**MillerCalib**

‘. And check out the colour version of ‘**HLfit**

‘:**varPart**

`varPart(A = 0.456, B = 0.315, AB = 0.852, A.name = "Spatial", B.name = "Climatic", `

**col = TRUE**)`varPart(A = 0.456, B = 0.315, C = 0.281, AB = 0.051, BC = 0.444,`

AC = 0.569, ABC = 0.624, A.name = "Spatial", B.name = "Human",

C.name = "Climatic", **col = TRUE**)

Feel free to send me any bug reports! Feature requests/suggestions are also welcome, though I can’t promise a timely response… And remember to look for the latest **package updates in the development page on R-Forge**!

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