tests/testthat/_snaps/check_performance.md
In INCEPTdk/adaptr: Adaptive Trial Simulator
valid parameters work
Code
check_performance(res)
Output
metric est
1 n_summarised 20.000
2 size_mean 1250.000
3 size_sd 551.076
4 size_median 1200.000
5 size_p25 850.000
6 size_p75 1675.000
7 size_p0 400.000
8 size_p100 2000.000
9 sum_ys_mean 282.000
10 sum_ys_sd 125.760
11 sum_ys_median 269.500
12 sum_ys_p25 186.750
13 sum_ys_p75 384.000
14 sum_ys_p0 94.000
15 sum_ys_p100 472.000
16 ratio_ys_mean 0.226
17 ratio_ys_sd 0.012
18 ratio_ys_median 0.221
19 ratio_ys_p25 0.220
20 ratio_ys_p75 0.231
21 ratio_ys_p0 0.215
22 ratio_ys_p100 0.270
23 prob_conclusive 0.800
24 prob_superior 0.650
25 prob_equivalence 0.150
26 prob_futility 0.000
27 prob_max 0.200
28 prob_select_arm_A 0.000
29 prob_select_arm_B 0.650
30 prob_select_arm_C 0.000
31 prob_select_none 0.350
32 rmse 0.020
33 rmse_te NA
34 mae 0.009
35 mae_te NA
36 idp 100.000
Code
check_performance(res, uncertainty = FALSE)
Output
metric est
1 n_summarised 20.000
2 size_mean 1250.000
3 size_sd 551.076
4 size_median 1200.000
5 size_p25 850.000
6 size_p75 1675.000
7 size_p0 400.000
8 size_p100 2000.000
9 sum_ys_mean 282.000
10 sum_ys_sd 125.760
11 sum_ys_median 269.500
12 sum_ys_p25 186.750
13 sum_ys_p75 384.000
14 sum_ys_p0 94.000
15 sum_ys_p100 472.000
16 ratio_ys_mean 0.226
17 ratio_ys_sd 0.012
18 ratio_ys_median 0.221
19 ratio_ys_p25 0.220
20 ratio_ys_p75 0.231
21 ratio_ys_p0 0.215
22 ratio_ys_p100 0.270
23 prob_conclusive 0.800
24 prob_superior 0.650
25 prob_equivalence 0.150
26 prob_futility 0.000
27 prob_max 0.200
28 prob_select_arm_A 0.000
29 prob_select_arm_B 0.650
30 prob_select_arm_C 0.000
31 prob_select_none 0.350
32 rmse 0.020
33 rmse_te NA
34 mae 0.009
35 mae_te NA
36 idp 100.000
Code
check_performance(res, uncertainty = TRUE, boot_seed = 4131, n_boot = 100)
Condition
Warning:
values for n_boot < 1000 are not recommended, as they may cause instable results.
Output
metric est err_sd err_mad lo_ci hi_ci
1 n_summarised 20.000 0.000 0.000 20.000 20.000
2 size_mean 1250.000 115.920 129.727 1031.875 1462.625
3 size_sd 551.076 58.032 59.628 415.681 653.692
4 size_median 1200.000 166.978 148.260 973.750 1600.000
5 size_p25 850.000 189.979 222.390 500.000 1176.250
6 size_p75 1675.000 231.369 352.118 1236.875 2000.000
7 size_p0 400.000 NA NA NA NA
8 size_p100 2000.000 NA NA NA NA
9 sum_ys_mean 282.000 26.300 27.132 232.823 330.822
10 sum_ys_sd 125.760 13.762 14.130 95.505 146.682
11 sum_ys_median 269.500 38.722 39.289 210.275 357.987
12 sum_ys_p25 186.750 38.798 45.590 129.819 260.275
13 sum_ys_p75 384.000 50.837 58.192 276.794 462.000
14 sum_ys_p0 94.000 NA NA NA NA
15 sum_ys_p100 472.000 NA NA NA NA
16 ratio_ys_mean 0.226 0.003 0.003 0.222 0.232
17 ratio_ys_sd 0.012 0.004 0.005 0.005 0.019
18 ratio_ys_median 0.221 0.003 0.002 0.220 0.229
19 ratio_ys_p25 0.220 0.001 0.001 0.216 0.221
20 ratio_ys_p75 0.231 0.004 0.004 0.222 0.235
21 ratio_ys_p0 0.215 NA NA NA NA
22 ratio_ys_p100 0.270 NA NA NA NA
23 prob_conclusive 0.800 0.087 0.074 0.624 0.950
24 prob_superior 0.650 0.103 0.111 0.450 0.800
25 prob_equivalence 0.150 0.079 0.074 0.000 0.300
26 prob_futility 0.000 0.000 0.000 0.000 0.000
27 prob_max 0.200 0.087 0.074 0.050 0.376
28 prob_select_arm_A 0.000 0.000 0.000 0.000 0.000
29 prob_select_arm_B 0.650 0.103 0.111 0.450 0.800
30 prob_select_arm_C 0.000 0.000 0.000 0.000 0.000
31 prob_select_none 0.350 0.103 0.111 0.200 0.550
32 rmse 0.020 0.004 0.003 0.011 0.026
33 rmse_te NA NA NA NA NA
34 mae 0.009 0.005 0.003 0.005 0.025
35 mae_te NA NA NA NA NA
36 idp 100.000 0.000 0.000 100.000 100.000
Code
check_performance(res, uncertainty = TRUE, ci_width = 0.75, boot_seed = 4131,
n_boot = 100)
Condition
Warning:
values for n_boot < 1000 are not recommended, as they may cause instable results.
Output
metric est err_sd err_mad lo_ci hi_ci
1 n_summarised 20.000 0.000 0.000 20.000 20.000
2 size_mean 1250.000 115.920 129.727 1116.875 1383.125
3 size_sd 551.076 58.032 59.628 471.321 600.569
4 size_median 1200.000 166.978 148.260 1000.000 1400.000
5 size_p25 850.000 189.979 222.390 600.000 1000.000
6 size_p75 1675.000 231.369 352.118 1418.750 2000.000
7 size_p0 400.000 NA NA NA NA
8 size_p100 2000.000 NA NA NA NA
9 sum_ys_mean 282.000 26.300 27.132 252.144 313.913
10 sum_ys_sd 125.760 13.762 14.130 106.971 138.581
11 sum_ys_median 269.500 38.722 39.289 220.000 303.000
12 sum_ys_p25 186.750 38.798 45.590 135.000 220.000
13 sum_ys_p75 384.000 50.837 58.192 314.719 433.000
14 sum_ys_p0 94.000 NA NA NA NA
15 sum_ys_p100 472.000 NA NA NA NA
16 ratio_ys_mean 0.226 0.003 0.003 0.223 0.229
17 ratio_ys_sd 0.012 0.004 0.005 0.006 0.016
18 ratio_ys_median 0.221 0.003 0.002 0.220 0.225
19 ratio_ys_p25 0.220 0.001 0.001 0.218 0.220
20 ratio_ys_p75 0.231 0.004 0.004 0.225 0.235
21 ratio_ys_p0 0.215 NA NA NA NA
22 ratio_ys_p100 0.270 NA NA NA NA
23 prob_conclusive 0.800 0.087 0.074 0.700 0.900
24 prob_superior 0.650 0.103 0.111 0.500 0.750
25 prob_equivalence 0.150 0.079 0.074 0.050 0.250
26 prob_futility 0.000 0.000 0.000 0.000 0.000
27 prob_max 0.200 0.087 0.074 0.100 0.300
28 prob_select_arm_A 0.000 0.000 0.000 0.000 0.000
29 prob_select_arm_B 0.650 0.103 0.111 0.500 0.750
30 prob_select_arm_C 0.000 0.000 0.000 0.000 0.000
31 prob_select_none 0.350 0.103 0.111 0.250 0.500
32 rmse 0.020 0.004 0.003 0.014 0.023
33 rmse_te NA NA NA NA NA
34 mae 0.009 0.005 0.003 0.007 0.018
35 mae_te NA NA NA NA NA
36 idp 100.000 0.000 0.000 100.000 100.000
Code
check_performance(res, restrict = "superior")
Output
metric est
1 n_summarised 13.000
2 size_mean 1084.615
3 size_sd 493.028
4 size_median 1200.000
5 size_p25 600.000
6 size_p75 1400.000
7 size_p0 400.000
8 size_p100 1900.000
9 sum_ys_mean 244.000
10 sum_ys_sd 107.973
11 sum_ys_median 266.000
12 sum_ys_p25 135.000
13 sum_ys_p75 303.000
14 sum_ys_p0 94.000
15 sum_ys_p100 420.000
16 ratio_ys_mean 0.227
17 ratio_ys_sd 0.014
18 ratio_ys_median 0.222
19 ratio_ys_p25 0.220
20 ratio_ys_p75 0.228
21 ratio_ys_p0 0.216
22 ratio_ys_p100 0.270
23 prob_conclusive 1.000
24 prob_superior 1.000
25 prob_equivalence 0.000
26 prob_futility 0.000
27 prob_max 0.000
28 prob_select_arm_A 0.000
29 prob_select_arm_B 1.000
30 prob_select_arm_C 0.000
31 prob_select_none 0.000
32 rmse 0.020
33 rmse_te NA
34 mae 0.009
35 mae_te NA
36 idp 100.000
Code
check_performance(res, restrict = "selected")
Output
metric est
1 n_summarised 13.000
2 size_mean 1084.615
3 size_sd 493.028
4 size_median 1200.000
5 size_p25 600.000
6 size_p75 1400.000
7 size_p0 400.000
8 size_p100 1900.000
9 sum_ys_mean 244.000
10 sum_ys_sd 107.973
11 sum_ys_median 266.000
12 sum_ys_p25 135.000
13 sum_ys_p75 303.000
14 sum_ys_p0 94.000
15 sum_ys_p100 420.000
16 ratio_ys_mean 0.227
17 ratio_ys_sd 0.014
18 ratio_ys_median 0.222
19 ratio_ys_p25 0.220
20 ratio_ys_p75 0.228
21 ratio_ys_p0 0.216
22 ratio_ys_p100 0.270
23 prob_conclusive 1.000
24 prob_superior 1.000
25 prob_equivalence 0.000
26 prob_futility 0.000
27 prob_max 0.000
28 prob_select_arm_A 0.000
29 prob_select_arm_B 1.000
30 prob_select_arm_C 0.000
31 prob_select_none 0.000
32 rmse 0.020
33 rmse_te NA
34 mae 0.009
35 mae_te NA
36 idp 100.000
Code
check_performance(res, restrict = "superior", uncertainty = TRUE, boot_seed = "base",
n_boot = 100)
Condition
Warning:
values for n_boot < 1000 are not recommended, as they may cause instable results.
Output
metric est err_sd err_mad lo_ci hi_ci
1 n_summarised 13.000 1.859 1.483 9.000 17.000
2 size_mean 1084.615 123.986 130.963 849.643 1305.357
3 size_sd 493.028 64.548 69.102 347.577 597.946
4 size_median 1200.000 231.802 0.000 600.000 1376.250
5 size_p25 600.000 244.294 148.260 500.000 1200.000
6 size_p75 1400.000 172.379 148.260 1200.000 1639.375
7 size_p0 400.000 NA NA NA NA
8 size_p100 1900.000 NA NA NA NA
9 sum_ys_mean 244.000 27.085 28.637 193.007 292.815
10 sum_ys_sd 107.973 13.743 13.825 75.508 129.319
11 sum_ys_median 266.000 50.890 10.378 135.000 301.100
12 sum_ys_p25 135.000 50.145 23.351 110.000 265.762
13 sum_ys_p75 303.000 38.952 26.872 266.000 372.000
14 sum_ys_p0 94.000 NA NA NA NA
15 sum_ys_p100 420.000 NA NA NA NA
16 ratio_ys_mean 0.227 0.004 0.004 0.221 0.236
17 ratio_ys_sd 0.014 0.006 0.006 0.003 0.022
18 ratio_ys_median 0.222 0.003 0.001 0.220 0.229
19 ratio_ys_p25 0.220 0.001 0.001 0.218 0.222
20 ratio_ys_p75 0.228 0.008 0.004 0.222 0.253
21 ratio_ys_p0 0.216 NA NA NA NA
22 ratio_ys_p100 0.270 NA NA NA NA
23 prob_conclusive 1.000 0.000 0.000 1.000 1.000
24 prob_superior 1.000 0.000 0.000 1.000 1.000
25 prob_equivalence 0.000 0.000 0.000 0.000 0.000
26 prob_futility 0.000 0.000 0.000 0.000 0.000
27 prob_max 0.000 0.000 0.000 0.000 0.000
28 prob_select_arm_A 0.000 0.000 0.000 0.000 0.000
29 prob_select_arm_B 1.000 0.000 0.000 1.000 1.000
30 prob_select_arm_C 0.000 0.000 0.000 0.000 0.000
31 prob_select_none 0.000 0.000 0.000 0.000 0.000
32 rmse 0.020 0.003 0.004 0.013 0.025
33 rmse_te NA NA NA NA NA
34 mae 0.009 0.005 0.003 0.006 0.025
35 mae_te NA NA NA NA NA
36 idp 100.000 0.000 0.000 100.000 100.000
Code
check_performance(res, restrict = "selected", uncertainty = TRUE, boot_seed = "base",
n_boot = 100)
Condition
Warning:
values for n_boot < 1000 are not recommended, as they may cause instable results.
Output
metric est err_sd err_mad lo_ci hi_ci
1 n_summarised 13.000 1.859 1.483 9.000 17.000
2 size_mean 1084.615 123.986 130.963 849.643 1305.357
3 size_sd 493.028 64.548 69.102 347.577 597.946
4 size_median 1200.000 231.802 0.000 600.000 1376.250
5 size_p25 600.000 244.294 148.260 500.000 1200.000
6 size_p75 1400.000 172.379 148.260 1200.000 1639.375
7 size_p0 400.000 NA NA NA NA
8 size_p100 1900.000 NA NA NA NA
9 sum_ys_mean 244.000 27.085 28.637 193.007 292.815
10 sum_ys_sd 107.973 13.743 13.825 75.508 129.319
11 sum_ys_median 266.000 50.890 10.378 135.000 301.100
12 sum_ys_p25 135.000 50.145 23.351 110.000 265.762
13 sum_ys_p75 303.000 38.952 26.872 266.000 372.000
14 sum_ys_p0 94.000 NA NA NA NA
15 sum_ys_p100 420.000 NA NA NA NA
16 ratio_ys_mean 0.227 0.004 0.004 0.221 0.236
17 ratio_ys_sd 0.014 0.006 0.006 0.003 0.022
18 ratio_ys_median 0.222 0.003 0.001 0.220 0.229
19 ratio_ys_p25 0.220 0.001 0.001 0.218 0.222
20 ratio_ys_p75 0.228 0.008 0.004 0.222 0.253
21 ratio_ys_p0 0.216 NA NA NA NA
22 ratio_ys_p100 0.270 NA NA NA NA
23 prob_conclusive 1.000 0.000 0.000 1.000 1.000
24 prob_superior 1.000 0.000 0.000 1.000 1.000
25 prob_equivalence 0.000 0.000 0.000 0.000 0.000
26 prob_futility 0.000 0.000 0.000 0.000 0.000
27 prob_max 0.000 0.000 0.000 0.000 0.000
28 prob_select_arm_A 0.000 0.000 0.000 0.000 0.000
29 prob_select_arm_B 1.000 0.000 0.000 1.000 1.000
30 prob_select_arm_C 0.000 0.000 0.000 0.000 0.000
31 prob_select_none 0.000 0.000 0.000 0.000 0.000
32 rmse 0.020 0.003 0.004 0.013 0.025
33 rmse_te NA NA NA NA NA
34 mae 0.009 0.005 0.003 0.006 0.025
35 mae_te NA NA NA NA NA
36 idp 100.000 0.000 0.000 100.000 100.000
INCEPTdk/adaptr documentation built on May 7, 2024, 8:21 a.m.
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valid parameters work
Code
check_performance(res)
Output
metric est
1 n_summarised 20.000
2 size_mean 1250.000
3 size_sd 551.076
4 size_median 1200.000
5 size_p25 850.000
6 size_p75 1675.000
7 size_p0 400.000
8 size_p100 2000.000
9 sum_ys_mean 282.000
10 sum_ys_sd 125.760
11 sum_ys_median 269.500
12 sum_ys_p25 186.750
13 sum_ys_p75 384.000
14 sum_ys_p0 94.000
15 sum_ys_p100 472.000
16 ratio_ys_mean 0.226
17 ratio_ys_sd 0.012
18 ratio_ys_median 0.221
19 ratio_ys_p25 0.220
20 ratio_ys_p75 0.231
21 ratio_ys_p0 0.215
22 ratio_ys_p100 0.270
23 prob_conclusive 0.800
24 prob_superior 0.650
25 prob_equivalence 0.150
26 prob_futility 0.000
27 prob_max 0.200
28 prob_select_arm_A 0.000
29 prob_select_arm_B 0.650
30 prob_select_arm_C 0.000
31 prob_select_none 0.350
32 rmse 0.020
33 rmse_te NA
34 mae 0.009
35 mae_te NA
36 idp 100.000
Code
check_performance(res, uncertainty = FALSE)
Output
metric est
1 n_summarised 20.000
2 size_mean 1250.000
3 size_sd 551.076
4 size_median 1200.000
5 size_p25 850.000
6 size_p75 1675.000
7 size_p0 400.000
8 size_p100 2000.000
9 sum_ys_mean 282.000
10 sum_ys_sd 125.760
11 sum_ys_median 269.500
12 sum_ys_p25 186.750
13 sum_ys_p75 384.000
14 sum_ys_p0 94.000
15 sum_ys_p100 472.000
16 ratio_ys_mean 0.226
17 ratio_ys_sd 0.012
18 ratio_ys_median 0.221
19 ratio_ys_p25 0.220
20 ratio_ys_p75 0.231
21 ratio_ys_p0 0.215
22 ratio_ys_p100 0.270
23 prob_conclusive 0.800
24 prob_superior 0.650
25 prob_equivalence 0.150
26 prob_futility 0.000
27 prob_max 0.200
28 prob_select_arm_A 0.000
29 prob_select_arm_B 0.650
30 prob_select_arm_C 0.000
31 prob_select_none 0.350
32 rmse 0.020
33 rmse_te NA
34 mae 0.009
35 mae_te NA
36 idp 100.000
Code
check_performance(res, uncertainty = TRUE, boot_seed = 4131, n_boot = 100)
Condition
Warning:
values for n_boot < 1000 are not recommended, as they may cause instable results.
Output
metric est err_sd err_mad lo_ci hi_ci
1 n_summarised 20.000 0.000 0.000 20.000 20.000
2 size_mean 1250.000 115.920 129.727 1031.875 1462.625
3 size_sd 551.076 58.032 59.628 415.681 653.692
4 size_median 1200.000 166.978 148.260 973.750 1600.000
5 size_p25 850.000 189.979 222.390 500.000 1176.250
6 size_p75 1675.000 231.369 352.118 1236.875 2000.000
7 size_p0 400.000 NA NA NA NA
8 size_p100 2000.000 NA NA NA NA
9 sum_ys_mean 282.000 26.300 27.132 232.823 330.822
10 sum_ys_sd 125.760 13.762 14.130 95.505 146.682
11 sum_ys_median 269.500 38.722 39.289 210.275 357.987
12 sum_ys_p25 186.750 38.798 45.590 129.819 260.275
13 sum_ys_p75 384.000 50.837 58.192 276.794 462.000
14 sum_ys_p0 94.000 NA NA NA NA
15 sum_ys_p100 472.000 NA NA NA NA
16 ratio_ys_mean 0.226 0.003 0.003 0.222 0.232
17 ratio_ys_sd 0.012 0.004 0.005 0.005 0.019
18 ratio_ys_median 0.221 0.003 0.002 0.220 0.229
19 ratio_ys_p25 0.220 0.001 0.001 0.216 0.221
20 ratio_ys_p75 0.231 0.004 0.004 0.222 0.235
21 ratio_ys_p0 0.215 NA NA NA NA
22 ratio_ys_p100 0.270 NA NA NA NA
23 prob_conclusive 0.800 0.087 0.074 0.624 0.950
24 prob_superior 0.650 0.103 0.111 0.450 0.800
25 prob_equivalence 0.150 0.079 0.074 0.000 0.300
26 prob_futility 0.000 0.000 0.000 0.000 0.000
27 prob_max 0.200 0.087 0.074 0.050 0.376
28 prob_select_arm_A 0.000 0.000 0.000 0.000 0.000
29 prob_select_arm_B 0.650 0.103 0.111 0.450 0.800
30 prob_select_arm_C 0.000 0.000 0.000 0.000 0.000
31 prob_select_none 0.350 0.103 0.111 0.200 0.550
32 rmse 0.020 0.004 0.003 0.011 0.026
33 rmse_te NA NA NA NA NA
34 mae 0.009 0.005 0.003 0.005 0.025
35 mae_te NA NA NA NA NA
36 idp 100.000 0.000 0.000 100.000 100.000
Code
check_performance(res, uncertainty = TRUE, ci_width = 0.75, boot_seed = 4131,
n_boot = 100)
Condition
Warning:
values for n_boot < 1000 are not recommended, as they may cause instable results.
Output
metric est err_sd err_mad lo_ci hi_ci
1 n_summarised 20.000 0.000 0.000 20.000 20.000
2 size_mean 1250.000 115.920 129.727 1116.875 1383.125
3 size_sd 551.076 58.032 59.628 471.321 600.569
4 size_median 1200.000 166.978 148.260 1000.000 1400.000
5 size_p25 850.000 189.979 222.390 600.000 1000.000
6 size_p75 1675.000 231.369 352.118 1418.750 2000.000
7 size_p0 400.000 NA NA NA NA
8 size_p100 2000.000 NA NA NA NA
9 sum_ys_mean 282.000 26.300 27.132 252.144 313.913
10 sum_ys_sd 125.760 13.762 14.130 106.971 138.581
11 sum_ys_median 269.500 38.722 39.289 220.000 303.000
12 sum_ys_p25 186.750 38.798 45.590 135.000 220.000
13 sum_ys_p75 384.000 50.837 58.192 314.719 433.000
14 sum_ys_p0 94.000 NA NA NA NA
15 sum_ys_p100 472.000 NA NA NA NA
16 ratio_ys_mean 0.226 0.003 0.003 0.223 0.229
17 ratio_ys_sd 0.012 0.004 0.005 0.006 0.016
18 ratio_ys_median 0.221 0.003 0.002 0.220 0.225
19 ratio_ys_p25 0.220 0.001 0.001 0.218 0.220
20 ratio_ys_p75 0.231 0.004 0.004 0.225 0.235
21 ratio_ys_p0 0.215 NA NA NA NA
22 ratio_ys_p100 0.270 NA NA NA NA
23 prob_conclusive 0.800 0.087 0.074 0.700 0.900
24 prob_superior 0.650 0.103 0.111 0.500 0.750
25 prob_equivalence 0.150 0.079 0.074 0.050 0.250
26 prob_futility 0.000 0.000 0.000 0.000 0.000
27 prob_max 0.200 0.087 0.074 0.100 0.300
28 prob_select_arm_A 0.000 0.000 0.000 0.000 0.000
29 prob_select_arm_B 0.650 0.103 0.111 0.500 0.750
30 prob_select_arm_C 0.000 0.000 0.000 0.000 0.000
31 prob_select_none 0.350 0.103 0.111 0.250 0.500
32 rmse 0.020 0.004 0.003 0.014 0.023
33 rmse_te NA NA NA NA NA
34 mae 0.009 0.005 0.003 0.007 0.018
35 mae_te NA NA NA NA NA
36 idp 100.000 0.000 0.000 100.000 100.000
Code
check_performance(res, restrict = "superior")
Output
metric est
1 n_summarised 13.000
2 size_mean 1084.615
3 size_sd 493.028
4 size_median 1200.000
5 size_p25 600.000
6 size_p75 1400.000
7 size_p0 400.000
8 size_p100 1900.000
9 sum_ys_mean 244.000
10 sum_ys_sd 107.973
11 sum_ys_median 266.000
12 sum_ys_p25 135.000
13 sum_ys_p75 303.000
14 sum_ys_p0 94.000
15 sum_ys_p100 420.000
16 ratio_ys_mean 0.227
17 ratio_ys_sd 0.014
18 ratio_ys_median 0.222
19 ratio_ys_p25 0.220
20 ratio_ys_p75 0.228
21 ratio_ys_p0 0.216
22 ratio_ys_p100 0.270
23 prob_conclusive 1.000
24 prob_superior 1.000
25 prob_equivalence 0.000
26 prob_futility 0.000
27 prob_max 0.000
28 prob_select_arm_A 0.000
29 prob_select_arm_B 1.000
30 prob_select_arm_C 0.000
31 prob_select_none 0.000
32 rmse 0.020
33 rmse_te NA
34 mae 0.009
35 mae_te NA
36 idp 100.000
Code
check_performance(res, restrict = "selected")
Output
metric est
1 n_summarised 13.000
2 size_mean 1084.615
3 size_sd 493.028
4 size_median 1200.000
5 size_p25 600.000
6 size_p75 1400.000
7 size_p0 400.000
8 size_p100 1900.000
9 sum_ys_mean 244.000
10 sum_ys_sd 107.973
11 sum_ys_median 266.000
12 sum_ys_p25 135.000
13 sum_ys_p75 303.000
14 sum_ys_p0 94.000
15 sum_ys_p100 420.000
16 ratio_ys_mean 0.227
17 ratio_ys_sd 0.014
18 ratio_ys_median 0.222
19 ratio_ys_p25 0.220
20 ratio_ys_p75 0.228
21 ratio_ys_p0 0.216
22 ratio_ys_p100 0.270
23 prob_conclusive 1.000
24 prob_superior 1.000
25 prob_equivalence 0.000
26 prob_futility 0.000
27 prob_max 0.000
28 prob_select_arm_A 0.000
29 prob_select_arm_B 1.000
30 prob_select_arm_C 0.000
31 prob_select_none 0.000
32 rmse 0.020
33 rmse_te NA
34 mae 0.009
35 mae_te NA
36 idp 100.000
Code
check_performance(res, restrict = "superior", uncertainty = TRUE, boot_seed = "base",
n_boot = 100)
Condition
Warning:
values for n_boot < 1000 are not recommended, as they may cause instable results.
Output
metric est err_sd err_mad lo_ci hi_ci
1 n_summarised 13.000 1.859 1.483 9.000 17.000
2 size_mean 1084.615 123.986 130.963 849.643 1305.357
3 size_sd 493.028 64.548 69.102 347.577 597.946
4 size_median 1200.000 231.802 0.000 600.000 1376.250
5 size_p25 600.000 244.294 148.260 500.000 1200.000
6 size_p75 1400.000 172.379 148.260 1200.000 1639.375
7 size_p0 400.000 NA NA NA NA
8 size_p100 1900.000 NA NA NA NA
9 sum_ys_mean 244.000 27.085 28.637 193.007 292.815
10 sum_ys_sd 107.973 13.743 13.825 75.508 129.319
11 sum_ys_median 266.000 50.890 10.378 135.000 301.100
12 sum_ys_p25 135.000 50.145 23.351 110.000 265.762
13 sum_ys_p75 303.000 38.952 26.872 266.000 372.000
14 sum_ys_p0 94.000 NA NA NA NA
15 sum_ys_p100 420.000 NA NA NA NA
16 ratio_ys_mean 0.227 0.004 0.004 0.221 0.236
17 ratio_ys_sd 0.014 0.006 0.006 0.003 0.022
18 ratio_ys_median 0.222 0.003 0.001 0.220 0.229
19 ratio_ys_p25 0.220 0.001 0.001 0.218 0.222
20 ratio_ys_p75 0.228 0.008 0.004 0.222 0.253
21 ratio_ys_p0 0.216 NA NA NA NA
22 ratio_ys_p100 0.270 NA NA NA NA
23 prob_conclusive 1.000 0.000 0.000 1.000 1.000
24 prob_superior 1.000 0.000 0.000 1.000 1.000
25 prob_equivalence 0.000 0.000 0.000 0.000 0.000
26 prob_futility 0.000 0.000 0.000 0.000 0.000
27 prob_max 0.000 0.000 0.000 0.000 0.000
28 prob_select_arm_A 0.000 0.000 0.000 0.000 0.000
29 prob_select_arm_B 1.000 0.000 0.000 1.000 1.000
30 prob_select_arm_C 0.000 0.000 0.000 0.000 0.000
31 prob_select_none 0.000 0.000 0.000 0.000 0.000
32 rmse 0.020 0.003 0.004 0.013 0.025
33 rmse_te NA NA NA NA NA
34 mae 0.009 0.005 0.003 0.006 0.025
35 mae_te NA NA NA NA NA
36 idp 100.000 0.000 0.000 100.000 100.000
Code
check_performance(res, restrict = "selected", uncertainty = TRUE, boot_seed = "base",
n_boot = 100)
Condition
Warning:
values for n_boot < 1000 are not recommended, as they may cause instable results.
Output
metric est err_sd err_mad lo_ci hi_ci
1 n_summarised 13.000 1.859 1.483 9.000 17.000
2 size_mean 1084.615 123.986 130.963 849.643 1305.357
3 size_sd 493.028 64.548 69.102 347.577 597.946
4 size_median 1200.000 231.802 0.000 600.000 1376.250
5 size_p25 600.000 244.294 148.260 500.000 1200.000
6 size_p75 1400.000 172.379 148.260 1200.000 1639.375
7 size_p0 400.000 NA NA NA NA
8 size_p100 1900.000 NA NA NA NA
9 sum_ys_mean 244.000 27.085 28.637 193.007 292.815
10 sum_ys_sd 107.973 13.743 13.825 75.508 129.319
11 sum_ys_median 266.000 50.890 10.378 135.000 301.100
12 sum_ys_p25 135.000 50.145 23.351 110.000 265.762
13 sum_ys_p75 303.000 38.952 26.872 266.000 372.000
14 sum_ys_p0 94.000 NA NA NA NA
15 sum_ys_p100 420.000 NA NA NA NA
16 ratio_ys_mean 0.227 0.004 0.004 0.221 0.236
17 ratio_ys_sd 0.014 0.006 0.006 0.003 0.022
18 ratio_ys_median 0.222 0.003 0.001 0.220 0.229
19 ratio_ys_p25 0.220 0.001 0.001 0.218 0.222
20 ratio_ys_p75 0.228 0.008 0.004 0.222 0.253
21 ratio_ys_p0 0.216 NA NA NA NA
22 ratio_ys_p100 0.270 NA NA NA NA
23 prob_conclusive 1.000 0.000 0.000 1.000 1.000
24 prob_superior 1.000 0.000 0.000 1.000 1.000
25 prob_equivalence 0.000 0.000 0.000 0.000 0.000
26 prob_futility 0.000 0.000 0.000 0.000 0.000
27 prob_max 0.000 0.000 0.000 0.000 0.000
28 prob_select_arm_A 0.000 0.000 0.000 0.000 0.000
29 prob_select_arm_B 1.000 0.000 0.000 1.000 1.000
30 prob_select_arm_C 0.000 0.000 0.000 0.000 0.000
31 prob_select_none 0.000 0.000 0.000 0.000 0.000
32 rmse 0.020 0.003 0.004 0.013 0.025
33 rmse_te NA NA NA NA NA
34 mae 0.009 0.005 0.003 0.006 0.025
35 mae_te NA NA NA NA NA
36 idp 100.000 0.000 0.000 100.000 100.000
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