Studentized residuals vs fitted plot should return the threshold value

[aravindhebbali]

ols_dsrvsp_plot() should return the threshold value used to classify observations as outliers.

> library(caret)
> data("Sacramento")
> lm_fit2 <- lm(price  ~ beds + baths + log(sqft), data = Sacramento)
> k <- ols_dsrvsp_plot(lm_fit2)

> k$Observation
 [1] 153 154 157 158 173 292 294 313 321 322 329 331 332 333 334 366 382 511
[19] 519 542 543 548 549 550 551 552 553 612 705 781 784 794 801 803 807 808
[37] 811 813 814

> k$`Fitted Values`
 [1] 360772.40 381583.73 383950.67 515681.86 267446.73 -33842.84 148765.08
 [8] 218837.66 299506.69 293232.33 329874.54 435111.42 387833.36 328982.41
[15] 247340.74 309322.96 316369.22 192166.95 173431.54 317974.74 207462.00
[22] 390030.50 460137.30 381167.93 336377.25 462055.20 452521.77 355958.76
[29] 463038.32 232302.16 238606.40 284384.56 207829.30 220043.13 352189.48
[36] 353470.84 435119.40 499025.57 541641.87

> k$`Deleted Studentized Residual`
 [1]  2.131717  2.434828  3.315315  3.807551 -2.016768  4.447093  2.274949
 [8]  2.710143  2.208636  2.292741  3.020921  2.141023  3.546566  4.471201
[15]  7.311647 -2.275739 -2.153874  2.006514  2.445023  2.174906  3.588165
[22]  2.945940  2.494206  3.543963  4.098482  2.753821  3.699032 -2.221324
[29] -2.327895  2.168987  2.231032  2.276834  4.058212  4.278508  2.967438
[36]  2.951958  2.243076  4.593773  4.147903

[aravindhebbali]

ols_dsrvsp_plot() returns the threshold value used to classify observations as outliers.

> library(olsrr)
> library(caret)
> data("Sacramento")
> lm_fit2 <- lm(price  ~ beds + baths + log(sqft), data = Sacramento)
> k <- ols_dsrvsp_plot(lm_fit2)

> k$outliers
# A tibble: 39 × 3
   Observation `Fitted Values` `Deleted Studentized Residual`
         <int>           <dbl>                          <dbl>
1          153       360772.40                       2.131717
2          154       381583.73                       2.434828
3          157       383950.67                       3.315315
4          158       515681.86                       3.807551
5          173       267446.73                      -2.016768
6          292       -33842.84                       4.447093
7          294       148765.08                       2.274949
8          313       218837.66                       2.710143
9          321       299506.69                       2.208636
10         322       293232.33                       2.292741
# ... with 29 more rows
Warning message:
In getNamespace("grid") : reached elapsed time limit

> k$threshold
[1] 2