R/ffp_opt_anlyz.R
ffp_opt_anlyz_rhgin_bin.RdWorks with binary allocation problems. The function invokes ffp_opt_sobin_target_row. The example tests think of as bottled protein.
ffp_opt_anlyz_rhgin_bin(
df,
svr_id_i,
svr_A_i = "A",
svr_alpha_i = "alpha",
svr_beta_i = "beta",
ar_rho = c(0.5, 0.1, -1, -20),
svr_rho = "rho",
svr_rho_val = "rho_val",
svr_inpalc = "rank",
svr_expout = "opti_exp_outcome",
verbose = FALSE
)tibble data table including variables using svr names below each row is potentially an individual who will receive alternative allocations
string name of the identify key for each i, to make sure merging happens properly
string name of the A_i variable, dot product of covariates and coefficients
string name of the alpha_i variable, individual specific elasticity information
string name of the beta_i variable, relative preference weight for each child
array preferences for equality for the planner, each value from negative infinity to 1
string variable name for the index planner inequality aversion variable, initially rho, then called rho, this is the index variable, index for each one of the rho values
string variable name for the value of the planner inequality aversion variable
string variable name for newly generated input optimal allocation
string variable name for newly generated expected outcome
boolean print out intermediary function outputs
a list with a dataframe and an array
df_all_rho - table where optimal targets given rhos are additional columns, note rank_max = highest rank reachest, lowest number
df_all_rho_long - long version of df_all_rho, single column all targets another column rho values
https://fanwangecon.github.io/PrjOptiAlloc/reference/ffp_opt_anlyz_rhgin_bin.html https://fanwangecon.github.io/PrjOptiAlloc/articles/ffv_opt_sobin_rkone_allrw_car.html
library(dplyr)
data(df_opt_dtgch_cbem4)
df <- df_opt_dtgch_cbem4
svr_id_i <- 'indi.id'
svr_A_i <- 'A_lin'
svr_alpha_i <- 'alpha_lin'
svr_beta_i <- 'beta'
ar_rho = c(-50, -10, -0.1, 0.1, 0.5, 0.7)
ls_bin_solu_all_rhos <- ffp_opt_anlyz_rhgin_bin(df, svr_id_i, svr_A_i, svr_alpha_i, svr_beta_i, ar_rho)
#> Joining, by = "indi.id"
df_all_rho <- ls_bin_solu_all_rhos$df_all_rho
head(df_all_rho %>% select(svr_id_i, svr_A_i, svr_alpha_i, starts_with("rho")), 30)
#> Note: Using an external vector in selections is ambiguous.
#> i Use `all_of(svr_id_i)` instead of `svr_id_i` to silence this message.
#> i See <https://tidyselect.r-lib.org/reference/faq-external-vector.html>.
#> This message is displayed once per session.
#> Note: Using an external vector in selections is ambiguous.
#> i Use `all_of(svr_A_i)` instead of `svr_A_i` to silence this message.
#> i See <https://tidyselect.r-lib.org/reference/faq-external-vector.html>.
#> This message is displayed once per session.
#> Note: Using an external vector in selections is ambiguous.
#> i Use `all_of(svr_alpha_i)` instead of `svr_alpha_i` to silence this message.
#> i See <https://tidyselect.r-lib.org/reference/faq-external-vector.html>.
#> This message is displayed once per session.
#> # A tibble: 30 x 9
#> indi.id A_lin alpha_lin rho_c1_rk rho_c2_rk rho_c3_rk rho_c4_rk rho_c5_rk
#> <dbl> <dbl> <dbl> <int> <int> <int> <int> <int>
#> 1 2 78.4 0.0101 937 967 967 967 967
#> 2 3 79.9 0.0323 853 669 669 669 669
#> 3 4 78.9 0.0323 583 578 578 578 578
#> 4 5 80.6 0.0662 734 521 202 201 201
#> 5 6 77.8 0.0101 787 861 861 861 861
#> 6 7 79.6 0.0662 484 428 125 125 125
#> 7 8 77.8 0.0101 793 865 865 865 865
#> 8 9 78.0 0.0101 823 883 883 883 883
#> 9 10 80.0 0.0662 572 483 166 166 166
#> 10 11 77.7 0.0602 126 126 358 358 358
#> # ... with 20 more rows, and 1 more variable: rho_c6_rk <int>
head(df_all_rho, 15)
#> # A tibble: 15 x 18
#> indi.id A_lin alpha_lin beta rank_min rank_max avg_rank S.country vil.id
#> <dbl> <dbl> <dbl> <dbl> <int> <int> <dbl> <chr> <dbl>
#> 1 2 78.4 0.0101 0.000959 967 937 962 Cebu 1
#> 2 3 79.9 0.0323 0.000959 853 669 700. Cebu 1
#> 3 4 78.9 0.0323 0.000959 583 578 579. Cebu 1
#> 4 5 80.6 0.0662 0.000959 734 201 343. Cebu 1
#> 5 6 77.8 0.0101 0.000959 861 787 849. Cebu 1
#> 6 7 79.6 0.0662 0.000959 484 125 235. Cebu 1
#> 7 8 77.8 0.0101 0.000959 865 793 853 Cebu 1
#> 8 9 78.0 0.0101 0.000959 883 823 873 Cebu 1
#> 9 10 80.0 0.0662 0.000959 572 166 286. Cebu 1
#> 10 11 77.7 0.0602 0.000959 358 126 281. Cebu 1
#> 11 12 77.7 0.0602 0.000959 350 117 272. Cebu 1
#> 12 13 78.9 0.0323 0.000959 585 579 580 Cebu 1
#> 13 14 78.8 0.0602 0.000959 518 335 466 Cebu 1
#> 14 15 81.1 0.0662 0.000959 875 219 382. Cebu 1
#> 15 16 78.8 0.0323 0.000959 566 552 564. Cebu 1
#> # ... with 9 more variables: svymthRound <dbl>, alpha_log <dbl>, A_log <dbl>,
#> # rho_c1_rk <int>, rho_c2_rk <int>, rho_c3_rk <int>, rho_c4_rk <int>,
#> # rho_c5_rk <int>, rho_c6_rk <int>
summary(df_all_rho)
#> indi.id A_lin alpha_lin beta
#> Min. : 2.0 Min. :73.70 Min. :0.01014 Min. :0.0009588
#> 1st Qu.: 298.5 1st Qu.:77.73 1st Qu.:0.01014 1st Qu.:0.0009588
#> Median : 627.0 Median :78.45 Median :0.06018 Median :0.0009588
#> Mean : 634.8 Mean :78.46 Mean :0.04108 Mean :0.0009588
#> 3rd Qu.: 939.5 3rd Qu.:79.15 3rd Qu.:0.06018 3rd Qu.:0.0009588
#> Max. :1349.0 Max. :84.61 Max. :0.06619 Max. :0.0009588
#> rank_min rank_max avg_rank S.country
#> Min. : 176.0 Min. : 1.0 Min. : 44.67 Length:1043
#> 1st Qu.: 414.0 1st Qu.: 131.0 1st Qu.: 266.25 Class :character
#> Median : 594.0 Median : 317.0 Median : 470.33 Mode :character
#> Mean : 625.5 Mean : 418.4 Mean : 522.00
#> 3rd Qu.: 837.5 3rd Qu.: 677.5 3rd Qu.: 756.75
#> Max. :1043.0 Max. :1036.0 Max. :1041.83
#> vil.id svymthRound alpha_log A_log
#> Min. : 1.00 Min. :24 Min. :0.006687 Min. :4.287
#> 1st Qu.: 7.00 1st Qu.:24 1st Qu.:0.006687 1st Qu.:4.334
#> Median :12.00 Median :24 Median :0.012090 Median :4.343
#> Mean :12.52 Mean :24 Mean :0.010321 Mean :4.343
#> 3rd Qu.:17.00 3rd Qu.:24 3rd Qu.:0.012090 3rd Qu.:4.351
#> Max. :33.00 Max. :24 Max. :0.013940 Max. :4.417
#> rho_c1_rk rho_c2_rk rho_c3_rk rho_c4_rk
#> Min. : 1.0 Min. : 1.0 Min. : 1.0 Min. : 1.0
#> 1st Qu.: 261.5 1st Qu.: 261.5 1st Qu.: 261.5 1st Qu.: 261.5
#> Median : 522.0 Median : 522.0 Median : 522.0 Median : 522.0
#> Mean : 522.0 Mean : 522.0 Mean : 522.0 Mean : 522.0
#> 3rd Qu.: 782.5 3rd Qu.: 782.5 3rd Qu.: 782.5 3rd Qu.: 782.5
#> Max. :1043.0 Max. :1043.0 Max. :1043.0 Max. :1043.0
#> rho_c5_rk rho_c6_rk
#> Min. : 1.0 Min. : 1.0
#> 1st Qu.: 261.5 1st Qu.: 261.5
#> Median : 522.0 Median : 522.0
#> Mean : 522.0 Mean : 522.0
#> 3rd Qu.: 782.5 3rd Qu.: 782.5
#> Max. :1043.0 Max. :1043.0
df_all_rho_long <- ls_bin_solu_all_rhos$df_all_rho_long
head(df_all_rho_long, 15)
#> # A tibble: 15 x 7
#> indi.id A_lin alpha_lin beta rho rho_val rank
#> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <int>
#> 1 2 78.4 0.0101 0.000959 1 -50 937
#> 2 2 78.4 0.0101 0.000959 2 -10 967
#> 3 2 78.4 0.0101 0.000959 3 -0.1 967
#> 4 2 78.4 0.0101 0.000959 4 0.1 967
#> 5 2 78.4 0.0101 0.000959 5 0.5 967
#> 6 2 78.4 0.0101 0.000959 6 0.7 967
#> 7 3 79.9 0.0323 0.000959 1 -50 853
#> 8 3 79.9 0.0323 0.000959 2 -10 669
#> 9 3 79.9 0.0323 0.000959 3 -0.1 669
#> 10 3 79.9 0.0323 0.000959 4 0.1 669
#> 11 3 79.9 0.0323 0.000959 5 0.5 669
#> 12 3 79.9 0.0323 0.000959 6 0.7 669
#> 13 4 78.9 0.0323 0.000959 1 -50 583
#> 14 4 78.9 0.0323 0.000959 2 -10 578
#> 15 4 78.9 0.0323 0.000959 3 -0.1 578
summary(df_all_rho_long)
#> indi.id A_lin alpha_lin beta
#> Min. : 2.0 Min. :73.70 Min. :0.01014 Min. :0.0009588
#> 1st Qu.: 298.0 1st Qu.:77.72 1st Qu.:0.01014 1st Qu.:0.0009588
#> Median : 627.0 Median :78.45 Median :0.06018 Median :0.0009588
#> Mean : 634.8 Mean :78.46 Mean :0.04108 Mean :0.0009588
#> 3rd Qu.: 940.0 3rd Qu.:79.15 3rd Qu.:0.06018 3rd Qu.:0.0009588
#> Max. :1349.0 Max. :84.61 Max. :0.06619 Max. :0.0009588
#> rho rho_val rank
#> Min. :1.0 Min. :-50.0 Min. : 1
#> 1st Qu.:2.0 1st Qu.:-10.0 1st Qu.: 261
#> Median :3.5 Median : 0.0 Median : 522
#> Mean :3.5 Mean : -9.8 Mean : 522
#> 3rd Qu.:5.0 3rd Qu.: 0.5 3rd Qu.: 783
#> Max. :6.0 Max. : 0.7 Max. :1043