goodness {forestPSD} | R Documentation |
Model quality assessment.
Description
Model quality assessment.
Usage
goodness(model,data)
Arguments
model |
A modle. |
data |
Dataset. |
Details
Model quality index as follow: MSE: the mean-squared-error; RMSE: the root-mean-squared-error; Rsquare: the variance of the predictions divided by the variance of the response; adj.Rsquare: adjusted the variance of the predictions divided by the variance of the response; MAE: the mean absolute error; MAPE: the mean absolute percentage error; RASE: the relative sum of absolute errors; AIC: Akaike's An Information Criterion; BIC: Schwarz's Bayesian criterion.
Value
Result returns the results model quality index.
Author(s)
Zongzheng Chai, chaizz@126.com
Examples
mod <- lm(mpg ~ wt, data = mtcars)
goodness(mod, mtcars)
[Package forestPSD version 1.0.0 Index]