Package: PAmeasures
Type: Package
Title: Prediction and Accuracy Measures for Nonlinear Models and for
        Right-Censored Time-to-Event Data
Version: 0.1.0
Date: 2018-01-18
Author: Xiaoyan Wang, Gang Li
Maintainer: Xiaoyan Wang<xywang@ucla.edu>
Description: 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.
Depends: R (>= 3.1)
Imports: survival, stats
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
Suggests: testthat
NeedsCompilation: no
Packaged: 2018-01-20 20:05:16 UTC; wywang-adm
Repository: CRAN
Date/Publication: 2018-01-22 10:06:41 UTC
Built: R 4.6.0; ; 2026-04-26 04:26:16 UTC; unix
