evaluate_plot: Prediction visualization

In glmaag: Adaptive LASSO and Network Regularized Generalized Linear Models

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

x <- rnorm(100)
y <- x + rnorm(100)
evaluate_plot(x, y)

glmaag documentation built on May 10, 2019, 9:04 a.m.