glmaag (version 0.0.6)

evaluate_plot: Prediction visualization

Description

Sample plots for prediction evaluation (scatter plot for Gaussian, ROC curve for logistic, and Kaplan Meier curve for Cox)

Usage

evaluate_plot(y_pre, y_test, fam = "Gaussian", mod, y_train, cutp)

Arguments

y_pre

predicted value

y_test

actual value

fam

type of predicted outcome, can be "Gaussian" (default), "Logisitc", and "Cox"

mod

fitted glmagarph model, must be available for Cox if cutpoint not provided

y_train

the training outcome to obtain

cutp

cutpoint for Cox model

Value

plots

Examples

# NOT RUN {
x <- rnorm(100)
y <- x + rnorm(100)
evaluate_plot(x, y)
# }