Package: PAmeasures 0.1.0

Xiaoyan Wang

PAmeasures: Prediction and Accuracy Measures for Nonlinear Models and for Right-Censored Time-to-Event Data

We propose a pair of summary measures for the predictive power of a prediction function based on a regression model. The regression model can be linear or nonlinear, parametric, semi-parametric, or nonparametric, and correctly specified or mis-specified. The first measure, R-squared, is an extension of the classical R-squared statistic for a linear model, quantifying the prediction function's ability to capture the variability of the response. The second measure, L-squared, quantifies the prediction function's bias for predicting the mean regression function. When used together, they give a complete summary of the predictive power of a prediction function. Please refer to Gang Li and Xiaoyan Wang (2016) <arxiv:1611.03063> for more details.

Authors:Xiaoyan Wang, Gang Li

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PAmeasures/json (API)

# Install 'PAmeasures' in R:
install.packages('PAmeasures', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

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1.18 score 1 stars 15 scripts 120 downloads 4 exports 3 dependencies

Last updated 7 years agofrom:d73a4eec65. Checks:OK: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 10 2024
R-4.5-linuxOKOct 10 2024

Exports:pam.censorpam.coxphpam.nlmpam.survreg

Dependencies:latticeMatrixsurvival