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]