tests/testthat/test-best-subsets-output.R

context("best subsets regression output")

test_that("output from best subsets regression is as expected", {
  x <- cat("   Best Subsets Regression
------------------------------
Model Index    Predictors
------------------------------
     1         wt
     2         hp wt
     3         hp wt qsec
     4         disp hp wt qsec
------------------------------

                                                  Subsets Regression Summary
-------------------------------------------------------------------------------------------------------------------------------
                       Adj.        Pred
Model    R-Square    R-Square    R-Square     C(p)        AIC        SBIC        SBC        MSEP      FPE       HSP       APC
-------------------------------------------------------------------------------------------------------------------------------
  1        0.7528      0.7446      0.7087    12.4809    166.0294    74.2916    170.4266    9.8972    9.8572    0.3199    0.2801
  2        0.8268      0.8148      0.7811     2.3690    156.6523    66.5755    162.5153    7.4314    7.3563    0.2402    0.2091
  3        0.8348      0.8171       0.782     3.0617    157.1426    67.7238    164.4713    7.6140    7.4756    0.2461    0.2124
  4        0.8351      0.8107       0.771     5.0000    159.0696    70.0408    167.8640    8.1810    7.9497    0.2644    0.2259
-------------------------------------------------------------------------------------------------------------------------------
AIC: Akaike Information Criteria
 SBIC: Sawa's Bayesian Information Criteria
 SBC: Schwarz Bayesian Criteria
 MSEP: Estimated error of prediction, assuming multivariate normality
 FPE: Final Prediction Error
 HSP: Hocking's Sp
 APC: Amemiya Prediction Criteria")

  model <- lm(mpg ~ disp + hp + wt + qsec, data = mtcars)
  expect_output(print(ols_step_best_subset(model)), x)
})
cmlopera/olsrr documentation built on May 26, 2019, 10:34 a.m.