R/ffp_opt_anlyz.R
ffp_opt_anlyz_rhgin.RdWorks with linear allocation problems. The function invokes ffp_opt_solin_relow, has parameters that are also required for that function. The addition here is *fl_rho* becomes *ar_rho*
ffp_opt_anlyz_rhgin(
df,
svr_id_i,
svr_A_i,
svr_alpha_i,
svr_beta_i,
fl_N_agg,
ar_rho,
svr_inpalc = "optiallocate",
svr_expout = "opti_exp_outcome"
)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 (marginal-effects)
string name of the beta_i variable, relative preference weight for each child
float total resource avaible for allocation, if not specific, sum by svr_N_i
array preferences for equality for the planner, each value from negative infinity to 1
string variable name for newly generated input optimal allocation
string variable name for newly generated expected outcome
a dataframe that expands the df inputs with additional results. a list with a dataframe and an array
df_opti_alloc_all_rho - table with columns for optimal allocation and exp outcome different rhos
mt_opti_alloc_all_rho - a matrix row = indi, col = rho, value = optimal allocation
mt_expc_outcm_all_rho - a matrix row = indi, col = rho, value = exp outcome optimal allocations
mt_gini - a matrix row = rhos, col = opti-allo and exp-out, value = gini
https://fanwangecon.github.io/PrjOptiAlloc/reference/ffp_opt_anlyz_rhgin.html https://fanwangecon.github.io/PrjOptiAlloc/articles/ffv_opt_anlyz_rhgin.html
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'
fl_N_agg <- 10000
ar_rho = c(-50, -10, -0.1, 0.1, 0.5, 0.7)
ls_lin_solu_all_rhos <- ffp_opt_anlyz_rhgin(df, svr_id_i, svr_A_i, svr_alpha_i, svr_beta_i, fl_N_agg, ar_rho)
df_opti_alloc_all_rho <- ls_lin_solu_all_rhos$df_opti_alloc_all_rho
summary(df_opti_alloc_all_rho)
#> S.country vil.id indi.id svymthRound
#> Length:1043 Min. : 1.00 Min. : 2.0 Min. :24
#> Class :character 1st Qu.: 7.00 1st Qu.: 298.5 1st Qu.:24
#> Mode :character Median :12.00 Median : 627.0 Median :24
#> Mean :12.52 Mean : 634.8 Mean :24
#> 3rd Qu.:17.00 3rd Qu.: 939.5 3rd Qu.:24
#> Max. :33.00 Max. :1349.0 Max. :24
#> alpha_lin alpha_log A_lin A_log
#> Min. :0.01014 Min. :0.006687 Min. :73.70 Min. :4.287
#> 1st Qu.:0.01014 1st Qu.:0.006687 1st Qu.:77.73 1st Qu.:4.334
#> Median :0.06018 Median :0.012090 Median :78.45 Median :4.343
#> Mean :0.04108 Mean :0.010321 Mean :78.46 Mean :4.343
#> 3rd Qu.:0.06018 3rd Qu.:0.012090 3rd Qu.:79.15 3rd Qu.:4.351
#> Max. :0.06619 Max. :0.013940 Max. :84.61 Max. :4.417
#> beta rho_c1_optiallocate rho_c1_opti_exp_outcome
#> Min. :0.0009588 Min. : 0.000 Min. :76.56
#> 1st Qu.:0.0009588 1st Qu.: 0.000 1st Qu.:78.35
#> Median :0.0009588 Median : 0.000 Median :79.28
#> Mean :0.0009588 Mean : 9.588 Mean :78.96
#> 3rd Qu.:0.0009588 3rd Qu.: 15.122 3rd Qu.:79.43
#> Max. :0.0009588 Max. :216.490 Max. :84.61
#> rho_c2_optiallocate rho_c2_opti_exp_outcome rho_c3_optiallocate
#> Min. : 0.000 Min. :74.37 Min. : 0.000
#> 1st Qu.: 0.000 1st Qu.:78.35 1st Qu.: 0.000
#> Median : 0.000 Median :79.35 Median : 0.000
#> Mean : 9.588 Mean :79.05 Mean : 9.588
#> 3rd Qu.:17.191 3rd Qu.:79.87 3rd Qu.: 0.000
#> Max. :94.000 Max. :84.61 Max. :63.897
#> rho_c3_opti_exp_outcome rho_c4_optiallocate rho_c4_opti_exp_outcome
#> Min. :74.37 Min. : 0.000 Min. :74.19
#> 1st Qu.:77.73 1st Qu.: 0.000 1st Qu.:77.73
#> Median :78.46 Median : 0.000 Median :78.46
#> Mean :79.10 Mean : 9.588 Mean :79.10
#> 3rd Qu.:79.87 3rd Qu.: 0.000 3rd Qu.:79.87
#> Max. :84.61 Max. :64.217 Max. :84.61
#> rho_c5_optiallocate rho_c5_opti_exp_outcome rho_c6_optiallocate
#> Min. : 0.000 Min. :73.70 Min. : 0.000
#> 1st Qu.: 0.000 1st Qu.:77.73 1st Qu.: 0.000
#> Median : 0.000 Median :78.46 Median : 0.000
#> Mean : 9.588 Mean :79.10 Mean : 9.588
#> 3rd Qu.: 0.000 3rd Qu.:79.87 3rd Qu.: 0.000
#> Max. :64.252 Max. :84.61 Max. :64.252
#> rho_c6_opti_exp_outcome
#> Min. :73.70
#> 1st Qu.:77.73
#> Median :78.46
#> Mean :79.10
#> 3rd Qu.:79.87
#> Max. :84.61
mt_opti_alloc_all_rho <- ls_lin_solu_all_rhos$mt_opti_alloc_all_rho
summary(mt_opti_alloc_all_rho)
#> rho_c1_optiallocate rho_c2_optiallocate rho_c3_optiallocate
#> Min. : 0.000 Min. : 0.000 Min. : 0.000
#> 1st Qu.: 0.000 1st Qu.: 0.000 1st Qu.: 0.000
#> Median : 0.000 Median : 0.000 Median : 0.000
#> Mean : 9.588 Mean : 9.588 Mean : 9.588
#> 3rd Qu.: 15.122 3rd Qu.:17.191 3rd Qu.: 0.000
#> Max. :216.490 Max. :94.000 Max. :63.897
#> rho_c4_optiallocate rho_c5_optiallocate rho_c6_optiallocate
#> Min. : 0.000 Min. : 0.000 Min. : 0.000
#> 1st Qu.: 0.000 1st Qu.: 0.000 1st Qu.: 0.000
#> Median : 0.000 Median : 0.000 Median : 0.000
#> Mean : 9.588 Mean : 9.588 Mean : 9.588
#> 3rd Qu.: 0.000 3rd Qu.: 0.000 3rd Qu.: 0.000
#> Max. :64.217 Max. :64.252 Max. :64.252
mt_expc_outcm_all_rho <- ls_lin_solu_all_rhos$mt_expc_outcm_all_rho
summary(mt_expc_outcm_all_rho)
#> rho_c1_opti_exp_outcome rho_c2_opti_exp_outcome rho_c3_opti_exp_outcome
#> Min. :76.56 Min. :74.37 Min. :74.37
#> 1st Qu.:78.35 1st Qu.:78.35 1st Qu.:77.73
#> Median :79.28 Median :79.35 Median :78.46
#> Mean :78.96 Mean :79.05 Mean :79.10
#> 3rd Qu.:79.43 3rd Qu.:79.87 3rd Qu.:79.87
#> Max. :84.61 Max. :84.61 Max. :84.61
#> rho_c4_opti_exp_outcome rho_c5_opti_exp_outcome rho_c6_opti_exp_outcome
#> Min. :74.19 Min. :73.70 Min. :73.70
#> 1st Qu.:77.73 1st Qu.:77.73 1st Qu.:77.73
#> Median :78.46 Median :78.46 Median :78.46
#> Mean :79.10 Mean :79.10 Mean :79.10
#> 3rd Qu.:79.87 3rd Qu.:79.87 3rd Qu.:79.87
#> Max. :84.61 Max. :84.61 Max. :84.61
mt_gini <- ls_lin_solu_all_rhos$mt_gini
summary(mt_gini)
#> it_rho_ctr optiallocate outcome planner_elas
#> Min. : 1.00 Min. :0.6902 Min. :0.006735 Min. :0.7029
#> 1st Qu.: 3.75 1st Qu.:0.7645 1st Qu.:0.009164 1st Qu.:0.7376
#> Median : 6.50 Median :0.8097 Median :0.013847 Median :1.1014
#> Mean : 6.50 Mean :0.7801 Mean :0.011644 Mean :1.1173
#> 3rd Qu.: 9.25 3rd Qu.:0.8107 3rd Qu.:0.013905 3rd Qu.:1.3863
#> Max. :12.00 Max. :0.8107 Max. :0.013908 Max. :1.6740
#> NA's :6 NA's :6