Benchmark with 1 and 8 processors - complex data

##   n_profile model        LL       AIC      BIC    SABIC     CAIC Entropy
## 1         4     2 -18659.68 -18659.68 37623.06 37502.32 37396.37   0.922
##   VLMR_val VLMR_p LMR_val LMR_p
## 1       NA     NA 465.075     0
##   n_profile model        LL       AIC      BIC    SABIC     CAIC Entropy
## 1         5     2 -18474.83 -18474.83 37301.33 37161.52 37039.03   0.901
##   VLMR_val VLMR_p LMR_val LMR_p
## 1       NA     NA 298.709     0
##   n_profiles model_2       V3
## 1          3      NA 38049.88
## 2          4      NA 37623.06
## 3          5      NA 37301.33
##   n_profile model        LL       AIC      BIC    SABIC     CAIC Entropy
## 1         4     2 -18659.68 -18659.68 37623.06 37502.32 37396.37   0.922
##   VLMR_val VLMR_p LMR_val LMR_p
## 1       NA     NA 465.075     0
##   n_profile model        LL       AIC      BIC    SABIC     CAIC Entropy
## 1         5     2 -18474.83 -18474.83 37301.33 37161.52 37039.03   0.901
##   VLMR_val VLMR_p LMR_val LMR_p
## 1       NA     NA 298.709     0
##   n_profiles model_2       V3
## 1          3      NA 38049.88
## 2          4      NA 37623.06
## 3          5      NA 37301.33
##   n_profile model        LL       AIC      BIC    SABIC     CAIC Entropy
## 1         4     2 -18659.68 -18659.68 37623.06 37502.32 37396.37   0.922
##   VLMR_val VLMR_p LMR_val LMR_p
## 1       NA     NA 465.075     0
##   n_profile model        LL       AIC      BIC    SABIC     CAIC Entropy
## 1         5     2 -18474.83 -18474.83 37301.33 37161.52 37039.03   0.901
##   VLMR_val VLMR_p LMR_val LMR_p
## 1       NA     NA 298.709     0
##   n_profiles model_2       V3
## 1          3      NA 38049.88
## 2          4      NA 37623.06
## 3          5      NA 37301.33
##   n_profile model        LL       AIC      BIC    SABIC     CAIC Entropy
## 1         4     2 -18659.68 -18659.68 37623.06 37502.32 37396.37   0.922
##   VLMR_val VLMR_p LMR_val LMR_p
## 1       NA     NA 465.075     0
##   n_profile model        LL       AIC      BIC    SABIC     CAIC Entropy
## 1         5     2 -18474.83 -18474.83 37301.33 37161.52 37039.03   0.901
##   VLMR_val VLMR_p LMR_val LMR_p
## 1       NA     NA 298.709     0
##   n_profiles model_2       V3
## 1          3      NA 38049.88
## 2          4      NA 37623.06
## 3          5      NA 37301.33
##   n_profile model        LL       AIC      BIC    SABIC     CAIC Entropy
## 1         4     2 -18659.68 -18659.68 37623.06 37502.32 37396.37   0.922
##   VLMR_val VLMR_p LMR_val LMR_p
## 1       NA     NA 465.075     0
##   n_profile model        LL       AIC      BIC    SABIC     CAIC Entropy
## 1         5     2 -18474.83 -18474.83 37301.33 37161.52 37039.03   0.901
##   VLMR_val VLMR_p LMR_val LMR_p
## 1       NA     NA 298.709     0
##   n_profiles model_2       V3
## 1          3      NA 38049.88
## 2          4      NA 37623.06
## 3          5      NA 37301.33
##   n_profile model        LL       AIC      BIC    SABIC     CAIC Entropy
## 1         4     2 -18659.68 -18659.68 37623.06 37502.32 37396.37   0.922
##   VLMR_val VLMR_p LMR_val LMR_p
## 1       NA     NA 465.075     0
##   n_profile model        LL       AIC      BIC    SABIC     CAIC Entropy
## 1         5     2 -18474.83 -18474.83 37301.33 37161.52 37039.03   0.901
##   VLMR_val VLMR_p LMR_val LMR_p
## 1       NA     NA 298.709     0
##   n_profiles model_2       V3
## 1          3      NA 38049.88
## 2          4      NA 37623.06
## 3          5      NA 37301.33
## Unit: seconds
##                                                                                                                                                                                                  expr
##  compare_solutions_mplus(df, dm_cog_eng, dm_beh_eng, dm_aff_eng,      dm_challenge, dm_competence, starts = c(600, 120), model = c(2),      n_profiles_min = 3, n_profiles_max = 5, n_processors = 8)
##  compare_solutions_mplus(df, dm_cog_eng, dm_beh_eng, dm_aff_eng,      dm_challenge, dm_competence, starts = c(600, 120), model = c(2),      n_profiles_min = 3, n_profiles_max = 5, n_processors = 1)
##       min       lq     mean   median       uq      max neval cld
##  136.9161 139.4207 142.9043 141.9253 145.8984 149.8715     3  a 
##  241.0798 241.3429 242.7772 241.6059 243.6259 245.6459     3   b