Output from reg_compute rounded up to 3 decimal points

[aravindhebbali]

The output from reg_compute() is rounded to 3 decimal points which leads to errors in the variable selection procedures.

> mtcars$cyl <- as.factor(mtcars$cyl)
> mtcars$gear <- as.factor(mtcars$gear)
> olsrr:::reg_comp(formula = mpg ~ disp + hp + log(wt) + cyl + gear * disp,  data = mtcars)
$r
[1] 0.95

$rsq
[1] 0.903

$adjr
[1] 0.864

$sigma
[1] 2.224

$cv
[1] 11.071

$mse
[1] 4.947

$mae
[1] 1.589

$aic
[1] 151.984

$sbc
[1] 168.107

$sbic
[1] 75.125

$prsq
[1] 0.802

$error_df
[1] 22

$model_df
[1] 9

$total_df
[1] 31

$ess
[1] 108.838

$rss
[1] 1017.209

$tss
[1] 1126.047

$rms
[1] 113.023

$ems
[1] 4.947

$f
[1] 22.847

$p
[1] 0

$n
[1] 7

$betas
(Intercept)        disp          hp     log(wt)        cyl6        cyl8       gear4 
     32.122       0.002      -0.030      -8.068      -0.595      -0.669       9.206 
      gear5  disp:gear4  disp:gear5 
      3.899      -0.054      -0.007 

$sbetas
      disp         hp    log(wt)       cyl6       cyl8      gear4      gear5 
     0.046     -0.344     -0.425     -0.041     -0.056      0.751      0.239 
disp:gear4 disp:gear5 
    -0.580     -0.093 

$std_errors
(Intercept)        disp          hp     log(wt)        cyl6        cyl8       gear4 
      3.312       0.011       0.017       3.578       1.554       2.793       4.035 
      gear5  disp:gear4  disp:gear5 
      3.417       0.027       0.013 

$tvalues
(Intercept)        disp          hp     log(wt)        cyl6        cyl8       gear4 
      9.698       0.200      -1.763      -2.255      -0.383      -0.239       2.282 
      gear5  disp:gear4  disp:gear5 
      1.141      -2.028      -0.505 

$pvalues
(Intercept)        disp          hp     log(wt)        cyl6        cyl8       gear4 
      0.000       0.844       0.092       0.034       0.706       0.813       0.033 
      gear5  disp:gear4  disp:gear5 
      0.266       0.055       0.618 

$df
[1] 1 1 1 1 1 1 1

$conf_lm
              2.5 % 97.5 %
(Intercept)  25.253 38.991
disp         -0.021  0.025
hp           -0.066  0.005
log(wt)     -15.488 -0.648
cyl6         -3.818  2.628
cyl8         -6.461  5.124
gear4         0.839 17.574
gear5        -3.187 10.985
disp:gear4   -0.109  0.001
disp:gear5   -0.034  0.020

$title
[1] "model"

$dependent
[1] "mpg"

$predictors
[1] "disp"    "hp"      "log(wt)" "cyl"     "gear"   

$mvars
 [1] "(Intercept)" "disp"        "hp"          "log(wt)"     "cyl6"       
 [6] "cyl8"        "gear4"       "gear5"       "disp:gear4"  "disp:gear5" 

$model

Call:
lm(formula = formula, data = data)

Coefficients:
(Intercept)         disp           hp      log(wt)         cyl6         cyl8  
  32.121919     0.002218    -0.030235    -8.067866    -0.594533    -0.668551  
      gear4        gear5   disp:gear4   disp:gear5  
   9.206104     3.899057    -0.053942    -0.006594  

Session Info

> sessionInfo()
R version 3.4.1 (2017-06-30)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows >= 8 x64 (build 9200)

Matrix products: default

locale:
[1] LC_COLLATE=English_India.1252  LC_CTYPE=English_India.1252   
[3] LC_MONETARY=English_India.1252 LC_NUMERIC=C                  
[5] LC_TIME=English_India.1252    

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

loaded via a namespace (and not attached):
 [1] Rcpp_0.12.11     tidyr_0.6.3      dplyr_0.7.1      assertthat_0.2.0
 [5] plyr_1.8.4       grid_3.4.1       R6_2.2.2         gtable_0.2.0    
 [9] magrittr_1.5     scales_0.4.1     ggplot2_2.2.1    rlang_0.1.1     
[13] lazyeval_0.2.0   bindrcpp_0.2     goftest_1.0-3    olsrr_0.2.0     
[17] nortest_1.0-4    tools_3.4.1      glue_1.1.1       purrr_0.2.2.2   
[21] munsell_0.4.3    compiler_3.4.1   colorspace_1.2-7 pkgconfig_2.0.1 
[25] bindr_0.1        gridExtra_2.2.1  tibble_1.3.3