stepAIC regression fails when model formula contains inline functions

[aravindhebbali]

ols_stepaic_both() returns an error when model formula contains inline functions.

> library(caret)
> data("Sacramento")
> lm_fit2 <- lm(price  ~ beds + baths + log(sqft), data = Sacramento)
> ols_stepaic_both(lm_fit2)
Error in eval(predvars, data, env) : object 'sqft' not found
Called from: eval(predvars, data, env)

> lm_fit1 <- lm(log(price)  ~ . - city, data = Sacramento)
> ols_stepaic_both(lm_fit1)
Error in eval(predvars, data, env) : object 'price' not found
Called from: eval(predvars, data, env)

Session Info

> sessionInfo()
R version 3.4.0 (2017-04-21)
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     

other attached packages:
[1] Rcpp_0.12.7     gridExtra_2.0.0 tidyr_0.6.0     tibble_1.2     
[5] purrr_0.2.2     dplyr_0.5.0     caret_6.0-76    ggplot2_2.2.1  
[9] lattice_0.20-35

loaded via a namespace (and not attached):
 [1] magrittr_1.5       splines_3.4.0      MASS_7.3-47       
 [4] munsell_0.4.3      colorspace_1.2-7   R6_2.2.1          
 [7] foreach_1.4.3      minqa_1.2.4        stringr_1.1.0     
[10] car_2.1-2          plyr_1.8.4         tools_3.4.0       
[13] parallel_3.4.0     nnet_7.3-12        pbkrtest_0.4-6    
[16] grid_3.4.0         gtable_0.2.0       nlme_3.1-125      
[19] mgcv_1.8-17        quantreg_5.19      DBI_0.5-1         
[22] MatrixModels_0.4-1 iterators_1.0.8    lme4_1.1-11       
[25] lazyeval_0.2.0     assertthat_0.2.0   Matrix_1.2-9      
[28] nloptr_1.0.4       reshape2_1.4.2     ModelMetrics_1.1.0
[31] codetools_0.2-15   stringi_1.1.2      compiler_3.4.0    
[34] scales_0.4.1       stats4_3.4.0       SparseM_1.7 

[aravindhebbali]

ols_stepaic_both() does not return an error when the model formula contains inline functions.

> library(olsrr)
> library(caret)
> data("Sacramento")

> lm_fit1 <- lm(log(price)  ~ . - city, data = Sacramento)
> ols_stepaic_both(lm_fit1)
No more variables to be added or removed.


                              Stepwise Summary                               
---------------------------------------------------------------------------
Variable     Method       AIC        RSS      Sum Sq     R-Sq     Adj. R-Sq 
---------------------------------------------------------------------------
sqft        addition    740.189    119.967    137.191    0.533        0.533 
zip         addition    470.175     77.767    179.391    0.698        0.674 
type        addition    421.418     73.487    183.671    0.714        0.691 
baths       addition    419.514      73.18    183.978    0.715        0.692 
---------------------------------------------------------------------------

> lm_fit2 <- lm(price  ~ beds + baths + log(sqft), data = Sacramento)
> ols_stepaic_both(lm_fit2)
No more variables to be added or removed.


                                     Stepwise Summary                                     
----------------------------------------------------------------------------------------
Variable      Method        AIC           RSS            Sum Sq       R-Sq     Adj. R-Sq 
----------------------------------------------------------------------------------------
log(sqft)    addition    23833.104    6917101778647.02    9090748642827.41    0.568        0.567 
beds         addition     23784.59    6552176660177.97    9455673761296.46    0.591         0.59 
----------------------------------------------------------------------------------------