In resplab/predtools: Prediction Model Tools

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/README-",
  out.width = "100%"
)

Overview

predtools provides miscellaneous tools for developing and evaluating prediction models.

Table of Contents

• Installation
• Example
• Model-based ROC
• Intercept Adjustment
• Calibration Plot
• Unit Normal Loss Integral in Two Dimensions

Installation {#installation}

You can install the released version of predtools from CRAN with:

install.packages("predtools")

And the development version from GitHub with:

# install.packages("remotes")
remotes::install_github("resplab/predtools")

Example {#example}

The function calibration_plot takes observed and predicted values from a prediction model and uses ggplot2 to produce a calibration plot:

library(predtools)
library(dplyr)
x <- rnorm(100, 10, 2)
y <- x + rnorm(100,0, 1)
data <- tibble(x,y)
calibration_plot(data, obs = "x", pred_1 = "y")

See vignettes for more advanced functionalities, including model-based ROC, intercept adjustment, calibration plot, and unit normal loss integral in two dimensions

You can also access the vignettes from R:

browseVignettes("predtools")

resplab/predtools documentation built on July 2, 2023, 2:58 a.m.