Übersicht/Clustering/Modelierung
Letzte Aktualisierung: 2025-07-09 19:51:51
Gesamtübersicht
Übersicht über CONTRAfluran-Filter
| agc.id | median.duration | mean.flow | mean.balanced.anaesthesia | mean.airway | mean.laparoscopic | n.cases.lama.nonlap.tiva | n.cases.tube.nonlap.tiva | n.cases.lama.lap.tiva | n.cases.tube.lap.tiva | n.cases.lama.nonlap.inha | n.cases.tube.nonlap.inha | n.cases.lama.lap.inha | n.cases.tube.lap.inha | sum.dura.lama.nonlap.tiva | sum.dura.tube.nonlap.tiva | sum.dura.lama.lap.tiva | sum.dura.tube.lap.tiva | sum.dura.lama.nonlap.inha | sum.dura.tube.nonlap.inha | sum.dura.lama.lap.inha | sum.dura.tube.lap.inha | med.flow.lama.nonlap.tiva | med.flow.tube.nonlap.tiva | med.flow.lama.lap.tiva | med.flow.tube.lap.tiva | med.flow.lama.nonlap.inha | med.flow.tube.nonlap.inha | med.flow.lama.lap.inha | med.flow.tube.lap.inha | ncases | available | weight1 | weight | center | or | water.trap | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 4 | CH0100022340 | 97.22 | 0.68 | 0.98 | 0.84 | 0.14 | 0 | 0 | 0 | 0 | 47 | 99 | 3 | 18 | 0.00 | 0.00 | 0 | 0.00 | 3075.32 | 14500.72 | 132.83 | 2737.72 | 0.00 | 0.00 | 0.0 | 0.00 | 0.35 | 0.30 | 0.50 | 0.32 | 171 | 1 | 1408.8 | 1408.8 | 4 | 04-06 | 0 |
| 5 | CH0100022358 | 87.60 | 0.51 | 0.98 | 0.95 | 0.32 | 0 | 0 | 0 | 1 | 4 | 24 | 2 | 14 | 0.00 | 0.00 | 0 | 98.77 | 157.95 | 3419.03 | 97.58 | 1486.18 | 0.00 | 0.00 | 0.0 | 3.00 | 0.50 | 0.38 | 0.52 | 0.30 | 46 | 1 | 1394.6 | 1394.6 | 4 | 04-05 | 0 |
| 6 | CH0100022359 | 47.85 | 1.95 | 0.74 | 0.57 | 0.00 | 2 | 8 | 0 | 0 | 19 | 11 | 0 | 0 | 165.33 | 461.93 | 0 | 0.00 | 856.65 | 904.28 | 0.00 | 0.00 | 3.00 | 3.00 | 0.0 | 0.00 | 0.50 | 0.35 | 0.00 | 0.00 | 40 | 1 | 1495.6 | 1495.6 | 4 | 04-01 | 0 |
| 7 | CH0100022374 | 140.29 | 0.48 | 0.94 | 0.99 | 0.01 | 0 | 7 | 0 | 0 | 3 | 201 | 0 | 1 | 0.00 | 1996.65 | 0 | 0.00 | 180.68 | 31157.87 | 0.00 | 270.90 | 0.00 | 0.55 | 0.0 | 0.00 | 0.30 | 0.35 | 0.00 | 0.25 | 212 | 1 | 1445.7 | 1445.7 | 4 | 04-03 | 0 |
| 8 | CH0100022440 | 111.97 | 0.46 | 0.63 | 0.72 | 0.00 | 3 | 3 | 0 | 0 | 3 | 10 | 0 | 0 | 359.13 | 455.38 | 0 | 0.00 | 288.18 | 1207.27 | 0.00 | 0.00 | 0.50 | 0.35 | 0.0 | 0.00 | 0.30 | 0.30 | 0.00 | 0.00 | 20 | 1 | 1368.1 | 1368.1 | 4 | 04-02 | 0 |
| 9 | CH0100022449 | 273.62 | 0.51 | 1.00 | 0.99 | 0.86 | 0 | 1 | 0 | 0 | 5 | 10 | 0 | 99 | 0.00 | 92.27 | 0 | 0.00 | 303.63 | 4424.45 | 0.00 | 29567.20 | 0.00 | 3.30 | 0.0 | 0.00 | 0.45 | 0.32 | 0.00 | 0.30 | 115 | 1 | 1450.4 | 1450.4 | 4 | 04-04 | 0 |
| 11 | CH0100022685 | 63.00 | 0.35 | 0.95 | 0.91 | 0.32 | 5 | 1 | 0 | 0 | 11 | 50 | 0 | 26 | 220.00 | 39.00 | 0 | 0.00 | 411.00 | 3900.00 | 0.00 | 2177.00 | 0.50 | 0.30 | 0.0 | 0.00 | 0.40 | 0.30 | 0.00 | 0.30 | 95 | 1 | 1445.7 | 1445.7 | 11 | 11-01 | 0 |
| 12 | CH0100022762 | 85.50 | 0.34 | 0.88 | 0.78 | 0.02 | 11 | 1 | 0 | 0 | 9 | 41 | 0 | 2 | 744.00 | 23.00 | 0 | 0.00 | 596.00 | 4681.00 | 0.00 | 153.00 | 0.30 | 1.00 | 0.0 | 0.00 | 0.30 | 0.30 | 0.00 | 0.30 | 64 | 1 | 1434.2 | 1434.2 | 11 | 11-02 | 0 |
| 13 | CH0100026809 | 62.00 | 0.00 | 0.00 | 0.00 | 0.00 | 2 | 1 | 0 | 0 | 9 | 44 | 0 | 11 | 57.00 | 44.00 | 0 | 0.00 | 227.00 | 4155.00 | 0.00 | 1051.00 | 0.30 | 0.35 | 0.0 | 0.00 | 0.30 | 0.30 | 0.00 | 0.30 | 69 | 1 | 1416.9 | 1416.9 | 11 | 11-01 | 0 |
| 15 | CH0100027240 | 84.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0 | 2 | 0 | 1 | 3 | 18 | 0 | 50 | 0.00 | 253.00 | 0 | 207.00 | 238.00 | 1338.00 | 0.00 | 5224.00 | 0.00 | 0.55 | 0.0 | 0.50 | 0.40 | 0.40 | 0.00 | 0.40 | 75 | 1 | 1413.4 | 1413.4 | 9 | 09-02 | 0 |
| 16 | CH0100027253 | 95.00 | 0.33 | 0.92 | 0.84 | 0.03 | 9 | 0 | 0 | 0 | 8 | 50 | 0 | 2 | 581.00 | 0.00 | 0 | 0.00 | 575.00 | 5829.00 | 0.00 | 204.00 | 0.30 | 0.00 | 0.0 | 0.00 | 0.38 | 0.30 | 0.00 | 0.55 | 69 | 1 | 1406.9 | 1406.9 | 11 | 11-02 | 0 |
| 17 | CH0100027255 | 61.00 | 0.32 | 0.99 | 0.86 | 0.38 | 1 | 0 | 0 | 0 | 15 | 32 | 0 | 25 | 28.00 | 0.00 | 0 | 0.00 | 696.00 | 2411.00 | 0.00 | 1942.00 | 0.30 | 0.00 | 0.0 | 0.00 | 0.35 | 0.30 | 0.00 | 0.30 | 73 | 1 | 1412.1 | 1412.1 | 11 | 11-01 | 0 |
| 18 | CH0100027395 | 62.00 | 0.32 | 1.00 | 0.85 | 0.39 | 1 | 0 | 0 | 0 | 8 | 16 | 0 | 13 | 14.00 | 0.00 | 0 | 0.00 | 440.00 | 1367.00 | 0.00 | 1157.00 | 0.50 | 0.00 | 0.0 | 0.00 | 0.30 | 0.30 | 0.00 | 0.30 | 38 | 1 | 1323.0 | 1323.0 | 11 | 11-01 | 0 |
| 19 | CH0100027397 | 95.00 | 0.34 | 0.94 | 0.75 | 0.00 | 13 | 3 | 0 | 0 | 34 | 93 | 0 | 0 | 643.00 | 230.00 | 0 | 0.00 | 2792.00 | 10263.00 | 0.00 | 0.00 | 0.30 | 0.30 | 0.0 | 0.00 | 0.38 | 0.30 | 0.00 | 0.00 | 143 | 1 | 1453.0 | 1453.0 | 11 | 11-02 | 0 |
| 20 | CH0100027403 | 92.00 | 0.33 | 0.90 | 0.61 | 0.02 | 8 | 1 | 0 | 0 | 22 | 31 | 0 | 1 | 522.00 | 63.00 | 0 | 0.00 | 1674.00 | 3205.00 | 0.00 | 130.00 | 0.30 | 0.30 | 0.0 | 0.00 | 0.30 | 0.30 | 0.00 | 0.30 | 63 | 1 | 1427.2 | 1427.2 | 11 | 11-02 | 0 |
| 22 | CH0100027412 | 63.00 | 0.33 | 0.98 | 0.90 | 0.31 | 4 | 0 | 0 | 0 | 10 | 51 | 0 | 23 | 106.00 | 0.00 | 0 | 0.00 | 589.00 | 4028.00 | 0.00 | 2133.00 | 0.90 | 0.00 | 0.0 | 0.00 | 0.40 | 0.30 | 0.00 | 0.30 | 89 | 1 | 1411.7 | 1411.7 | 11 | 11-01 | 0 |
| 43 | CH0100033346 | 47.32 | 0.98 | 0.93 | 0.58 | 0.01 | 1 | 7 | 0 | 0 | 34 | 21 | 0 | 1 | 12.55 | 288.00 | 0 | 0.00 | 1880.73 | 2254.38 | 0.00 | 25.63 | 15.00 | 3.00 | 0.0 | 0.00 | 0.50 | 0.30 | 0.00 | 0.50 | 65 | 1 | 1451.0 | 1451.0 | 4 | 04-01 | 0 |
| 44 | CH0100034686 | 70.00 | 0.50 | 0.88 | 0.99 | 0.00 | 0 | 12 | 0 | 0 | 1 | 64 | 0 | 0 | 0.00 | 738.00 | 0 | 0.00 | 40.00 | 5479.00 | 0.00 | 0.00 | 0.00 | 0.50 | 0.0 | 0.00 | 0.50 | 0.50 | 0.00 | 0.00 | 77 | 1 | 0.0 | 0.0 | 12 | 12-01 | 1 |
| 45 | CH0100034687 | 86.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0 | 10 | 0 | 0 | 0 | 67 | 0 | 0 | 0.00 | 599.00 | 0 | 0.00 | 0.00 | 6411.00 | 0.00 | 0.00 | 0.00 | 0.50 | 0.0 | 0.00 | 0.00 | 0.50 | 0.00 | 0.00 | 77 | 1 | 1471.1 | 1471.1 | 12 | 12-01 | 1 |
| 46 | CH0100035900 | 115.50 | 0.65 | 0.56 | 0.80 | 0.08 | 11 | 9 | 0 | 0 | 1 | 21 | 0 | 3 | 1055.00 | 1358.00 | 0 | 0.00 | 85.00 | 2730.00 | 0.00 | 436.00 | 0.70 | 0.50 | 0.0 | 0.00 | 0.80 | 0.50 | 0.00 | 0.50 | 46 | 1 | 1449.1 | 1449.1 | 6 | 06-01 | 0 |
| 49 | CH0100035906 | 149.00 | 0.69 | 0.80 | 0.92 | 0.80 | 7 | 1 | 0 | 2 | 0 | 4 | 0 | 17 | 427.00 | 88.00 | 0 | 533.00 | 0.00 | 526.00 | 0.00 | 3664.00 | 0.70 | 0.50 | 0.0 | 0.50 | 0.00 | 0.75 | 0.00 | 0.65 | 31 | 1 | 1494.9 | 1494.9 | 6 | 06-05 | 0 |
| 50 | CH0100035907 | 57.00 | 0.77 | 0.30 | 0.34 | 0.07 | 49 | 4 | 0 | 0 | 1 | 8 | 0 | 5 | 2706.00 | 293.00 | 0 | 0.00 | 107.00 | 885.00 | 0.00 | 295.00 | 1.00 | 0.50 | 0.0 | 0.00 | 0.80 | 0.65 | 0.00 | 0.65 | 67 | 1 | 1367.5 | 1367.5 | 6 | 06-06 | 0 |
| 52 | CH0100037143 | 77.33 | 1.11 | 1.00 | 0.92 | 0.33 | 0 | 0 | 0 | 0 | 4 | 14 | 1 | 6 | 0.00 | 0.00 | 0 | 0.00 | 173.02 | 1808.87 | 48.80 | 906.75 | 0.00 | 0.00 | 0.0 | 0.00 | 0.38 | 0.30 | 0.30 | 0.32 | 25 | 1 | 1262.9 | 1262.9 | 4 | 04-05 | 0 |
| 53 | CH0100037148 | 57.12 | 1.16 | 0.83 | 0.43 | 0.00 | 1 | 4 | 0 | 0 | 23 | 9 | 0 | 0 | 61.70 | 393.98 | 0 | 0.00 | 1433.18 | 736.85 | 0.00 | 0.00 | 0.20 | 0.65 | 0.0 | 0.00 | 0.50 | 0.50 | 0.00 | 0.00 | 37 | 1 | 1421.1 | 1421.1 | 4 | 04-01 | 0 |
| 54 | CH0100037286 | 81.56 | 0.99 | 0.82 | 0.85 | 0.02 | 7 | 47 | 0 | 0 | 38 | 118 | 0 | 3 | 459.25 | 3630.23 | 0 | 0.00 | 2880.95 | 14996.50 | 0.00 | 434.13 | 1.00 | 2.70 | 0.0 | 0.00 | 0.30 | 0.30 | 0.00 | 0.30 | 214 | 1 | 1380.6 | 1380.6 | 4 | 04-02 | 0 |
| 55 | CH0100037288 | 54.18 | 0.90 | 0.79 | 0.44 | 0.00 | 3 | 9 | 0 | 0 | 29 | 15 | 0 | 0 | 294.53 | 506.88 | 0 | 0.00 | 1901.33 | 1218.83 | 0.00 | 0.00 | 3.00 | 1.00 | 0.0 | 0.00 | 0.40 | 0.40 | 0.00 | 0.00 | 57 | 1 | 1423.2 | 1423.2 | 4 | 04-01 | 0 |
| 56 | CH0100037289 | 121.22 | 1.34 | 0.59 | 0.89 | 0.00 | 4 | 24 | 0 | 0 | 4 | 41 | 0 | 0 | 737.63 | 3435.72 | 0 | 0.00 | 412.03 | 5453.83 | 0.00 | 0.00 | 0.50 | 0.85 | 0.0 | 0.00 | 0.42 | 0.50 | 0.00 | 0.00 | 74 | 1 | 1363.5 | 1363.5 | 4 | 04-02 | 0 |
| 57 | CH0100037333 | 84.66 | 0.50 | 0.95 | 0.93 | 0.40 | 4 | 8 | 0 | 3 | 33 | 88 | 1 | 69 | 105.95 | 697.53 | 0 | 326.00 | 1386.90 | 10407.53 | 16.47 | 8218.93 | 8.50 | 2.50 | 0.0 | 0.50 | 0.40 | 0.35 | 0.50 | 0.30 | 206 | 1 | 1386.3 | 1386.3 | 4 | 04-05 | 0 |
| 59 | CH0100037348 | 52.53 | 1.03 | 0.63 | 0.53 | 0.00 | 4 | 13 | 0 | 0 | 22 | 10 | 0 | 0 | 285.43 | 865.25 | 0 | 0.00 | 1183.58 | 762.15 | 0.00 | 0.00 | 2.50 | 3.00 | 0.0 | 0.00 | 0.38 | 0.32 | 0.00 | 0.00 | 49 | 1 | 1376.0 | 1376.0 | 4 | 04-01 | 0 |
| 63 | CH0100037608 | 85.50 | 0.00 | 0.00 | 0.00 | 0.00 | 25 | 1 | 0 | 1 | 0 | 27 | 0 | 27 | 1558.00 | 55.00 | 0 | 65.00 | 0.00 | 3160.00 | 0.00 | 2985.00 | 0.80 | 0.60 | 0.0 | 0.60 | 0.00 | 0.50 | 0.00 | 0.50 | 82 | 1 | 1478.8 | 1478.8 | 6 | 06-04 | 1 |
| 67 | CH0100037620 | 113.00 | 0.77 | 0.57 | 0.80 | 0.05 | 18 | 10 | 0 | 0 | 1 | 31 | 0 | 5 | 1515.00 | 1943.00 | 0 | 0.00 | 97.00 | 4066.00 | 0.00 | 361.00 | 1.00 | 0.58 | 0.0 | 0.00 | 0.70 | 0.70 | 0.00 | 0.60 | 65 | 1 | 1455.1 | 1455.1 | 6 | 06-01 | 0 |
| 70 | CH0100037653 | 75.00 | 0.76 | 0.54 | 0.60 | 0.13 | 10 | 0 | 0 | 1 | 0 | 4 | 0 | 2 | 648.00 | 0.00 | 0 | 90.00 | 0.00 | 740.00 | 0.00 | 125.00 | 0.90 | 0.00 | 0.0 | 0.50 | 0.00 | 0.68 | 0.00 | 0.55 | 17 | 1 | 1172.4 | 1172.4 | 6 | 06-06 | 0 |
| 72 | CN0100000057 | 106.00 | 0.00 | 0.00 | 0.00 | 0.00 | 92 | 78 | 0 | 0 | 48 | 102 | 0 | 0 | 9124.00 | 9259.00 | 0 | 0.00 | 4431.00 | 13842.00 | 0.00 | 0.00 | 0.60 | 0.50 | 0.0 | 0.00 | 0.40 | 0.30 | 0.00 | 0.00 | 322 | 1 | 1407.8 | 1407.8 | 5 | 05-02 | 0 |
| 73 | CN0100000078 | 110.00 | 0.00 | 0.00 | 0.00 | 0.00 | 28 | 34 | 0 | 0 | 20 | 33 | 0 | 0 | 2935.00 | 4603.00 | 0 | 0.00 | 1741.00 | 4379.00 | 0.00 | 0.00 | 0.60 | 0.50 | 0.0 | 0.00 | 0.45 | 0.35 | 0.00 | 0.00 | 117 | 1 | 1390.1 | 1390.1 | 5 | 05-01 | 0 |
| 74 | CN0100000115 | 100.00 | 0.58 | 0.42 | 0.72 | 0.00 | 16 | 25 | 0 | 0 | 12 | 20 | 0 | 0 | 1337.00 | 3410.00 | 0 | 0.00 | 991.00 | 2489.00 | 0.00 | 0.00 | 0.60 | 0.60 | 0.0 | 0.00 | 0.30 | 0.40 | 0.00 | 0.00 | 74 | 1 | 1377.0 | 1377.0 | 5 | 05-01 | 0 |
| 75 | CN0100000175 | 90.00 | 0.58 | 0.66 | 0.71 | 0.00 | 6 | 7 | 0 | 0 | 7 | 13 | 0 | 0 | 413.00 | 925.00 | 0 | 0.00 | 698.00 | 1847.00 | 0.00 | 0.00 | 0.60 | 0.80 | 0.0 | 0.00 | 0.30 | 0.40 | 0.00 | 0.00 | 34 | 1 | 1312.2 | 1312.2 | 5 | 05-01 | 0 |
| 76 | CN0100000176 | 95.00 | 0.00 | 0.00 | 0.00 | 0.00 | 18 | 8 | 0 | 0 | 3 | 19 | 0 | 0 | 1622.00 | 833.00 | 0 | 0.00 | 129.00 | 2601.00 | 0.00 | 0.00 | 0.65 | 0.65 | 0.0 | 0.00 | 3.30 | 0.30 | 0.00 | 0.00 | 48 | 1 | 1305.1 | 1305.1 | 5 | 05-01 | 0 |
| 77 | CN0100000180 | 102.00 | 1.03 | 0.50 | 0.80 | 0.00 | 8 | 14 | 0 | 0 | 5 | 19 | 0 | 0 | 731.00 | 2323.00 | 0 | 0.00 | 482.00 | 2511.00 | 0.00 | 0.00 | 0.70 | 0.55 | 0.0 | 0.00 | 0.60 | 0.35 | 0.00 | 0.00 | 47 | 1 | 1387.8 | 1387.8 | 5 | 05-01 | 0 |
| 78 | CN0100000191 | 105.00 | 0.63 | 0.43 | 0.66 | 0.00 | 29 | 28 | 0 | 0 | 15 | 25 | 0 | 0 | 2814.00 | 3705.00 | 0 | 0.00 | 1066.00 | 3734.00 | 0.00 | 0.00 | 0.60 | 0.80 | 0.0 | 0.00 | 0.35 | 0.30 | 0.00 | 0.00 | 99 | 1 | 1404.3 | 1404.3 | 5 | 05-01 | 0 |
| 79 | CN0100000416 | 104.00 | 0.81 | 0.95 | 0.95 | 0.50 | 0 | 0 | 0 | 1 | 2 | 10 | 0 | 15 | 0.00 | 0.00 | 0 | 169.00 | 168.00 | 1601.00 | 0.00 | 1591.00 | 0.00 | 0.00 | 0.0 | 0.80 | 0.80 | 0.80 | 0.00 | 0.80 | 28 | 1 | 1487.1 | 1487.1 | 7 | 07-01 | 0 |
| 80 | CN0100000738 | 112.00 | 0.72 | 1.00 | 0.92 | 0.50 | 0 | 0 | 0 | 0 | 3 | 9 | 0 | 12 | 0.00 | 0.00 | 0 | 0.00 | 241.00 | 1170.00 | 0.00 | 1426.00 | 0.00 | 0.00 | 0.0 | 0.00 | 0.80 | 0.80 | 0.00 | 0.80 | 24 | 1 | 1480.7 | 1480.7 | 7 | 07-01 | 0 |
| 81 | CN0100000744 | 71.50 | 0.83 | 1.00 | 0.95 | 0.70 | 0 | 0 | 0 | 0 | 4 | 3 | 0 | 17 | 0.00 | 0.00 | 0 | 0.00 | 129.00 | 638.00 | 0.00 | 1786.00 | 0.00 | 0.00 | 0.0 | 0.00 | 0.80 | 0.80 | 0.00 | 0.80 | 24 | 1 | 1497.6 | 1497.6 | 7 | 07-01 | 0 |
| 82 | CN0100000757 | 88.00 | 1.12 | 1.00 | 0.98 | 0.48 | 0 | 0 | 0 | 0 | 1 | 8 | 1 | 12 | 0.00 | 0.00 | 0 | 0.00 | 20.00 | 1340.00 | 40.00 | 1191.00 | 0.00 | 0.00 | 0.0 | 0.00 | 0.80 | 0.80 | 0.80 | 0.80 | 22 | 1 | 1493.3 | 1493.3 | 7 | 07-01 | 0 |
| 83 | CN0100000760 | 97.00 | 0.84 | 0.92 | 0.91 | 0.39 | 0 | 1 | 0 | 0 | 4 | 9 | 0 | 9 | 0.00 | 213.00 | 0 | 0.00 | 227.00 | 1103.00 | 0.00 | 968.00 | 0.00 | 0.00 | 0.0 | 0.00 | 0.80 | 0.80 | 0.00 | 0.80 | 23 | 1 | 1484.7 | 1484.7 | 7 | 07-01 | 0 |
| 85 | CN0100001611 | 92.00 | 0.00 | 0.00 | 0.00 | 0.00 | 14 | 24 | 0 | 0 | 20 | 18 | 0 | 0 | 1272.00 | 2594.00 | 0 | 0.00 | 1890.00 | 2086.00 | 0.00 | 0.00 | 0.70 | 0.70 | 0.0 | 0.00 | 0.28 | 0.30 | 0.00 | 0.00 | 76 | 1 | 1368.2 | 1368.2 | 5 | 05-01 | 0 |
| 86 | CN0100001621 | 107.00 | 0.00 | 0.00 | 0.00 | 0.00 | 19 | 16 | 0 | 0 | 18 | 18 | 0 | 0 | 1681.00 | 1446.00 | 0 | 0.00 | 2043.00 | 2481.00 | 0.00 | 0.00 | 0.60 | 0.60 | 0.0 | 0.00 | 0.30 | 0.30 | 0.00 | 0.00 | 71 | 1 | 1377.8 | 1377.8 | 5 | 05-01 | 0 |
| 87 | CN0100002233 | 61.00 | 0.00 | 0.00 | 0.00 | 0.00 | 25 | 2 | 0 | 0 | 38 | 7 | 0 | 0 | 1709.00 | 119.00 | 0 | 0.00 | 2234.00 | 376.00 | 0.00 | 0.00 | 0.50 | 0.55 | 0.0 | 0.00 | 0.72 | 0.80 | 0.00 | 0.00 | 72 | 1 | 1555.4 | 1555.4 | 1 | 01-02 | 1 |
| 88 | CN0100002243 | 72.00 | 1.17 | 0.78 | 0.11 | 0.00 | 17 | 0 | 0 | 0 | 53 | 6 | 0 | 0 | 1333.00 | 0.00 | 0 | 0.00 | 3888.00 | 619.00 | 0.00 | 0.00 | 1.00 | 0.00 | 0.0 | 0.00 | 0.60 | 0.75 | 0.00 | 0.00 | 77 | 1 | 1533.6 | 1533.6 | 1 | 01-02 | 1 |
| 89 | CN0100002245 | 62.00 | 0.00 | 0.00 | 0.00 | 0.00 | 14 | 3 | 0 | 0 | 79 | 6 | 0 | 0 | 903.00 | 301.00 | 0 | 0.00 | 4963.00 | 401.00 | 0.00 | 0.00 | 0.65 | 0.95 | 0.0 | 0.00 | 0.55 | 0.50 | 0.00 | 0.00 | 103 | 1 | 1538.4 | 1538.4 | 1 | 01-02 | 1 |
| 90 | CN0100002251 | 52.50 | 0.00 | 0.00 | 0.00 | 0.00 | 7 | 1 | 0 | 0 | 58 | 6 | 0 | 0 | 424.00 | 53.00 | 0 | 0.00 | 3267.00 | 393.00 | 0.00 | 0.00 | 0.50 | 0.50 | 0.0 | 0.00 | 0.50 | 0.50 | 0.00 | 0.00 | 72 | 1 | 1520.5 | 1520.5 | 1 | 01-02 | 1 |
| 91 | CN0100002596 | 88.00 | 0.75 | 0.86 | 0.96 | 0.55 | 1 | 3 | 0 | 1 | 1 | 8 | 0 | 16 | 36.00 | 279.00 | 0 | 80.00 | 74.03 | 898.00 | 0.00 | 1469.00 | 0.80 | 0.60 | 0.0 | 0.75 | 0.70 | 0.70 | 0.00 | 0.80 | 30 | 1 | 1483.6 | 1483.6 | 6 | 06-03 | 0 |
| 92 | CN0100002597 | 102.00 | 0.78 | 0.63 | 0.75 | 0.04 | 9 | 5 | 0 | 0 | 1 | 22 | 0 | 3 | 1014.00 | 516.00 | 0 | 0.00 | 105.00 | 2631.00 | 0.00 | 171.00 | 1.00 | 0.40 | 0.0 | 0.00 | 1.00 | 0.70 | 0.00 | 0.50 | 42 | 1 | 1435.5 | 1435.5 | 6 | 06-01 | 0 |
| 93 | CN0100002598 | 88.00 | 0.58 | 0.81 | 0.87 | 0.27 | 7 | 2 | 0 | 0 | 0 | 12 | 0 | 8 | 369.00 | 168.00 | 0 | 0.00 | 0.00 | 1516.00 | 0.00 | 753.00 | 0.70 | 0.50 | 0.0 | 0.00 | 0.00 | 0.55 | 0.00 | 0.50 | 29 | 1 | 1400.8 | 1400.8 | 6 | 06-04 | 1 |
| 94 | CN0100002606 | 90.50 | 0.00 | 0.00 | 0.00 | 0.00 | 5 | 4 | 0 | 1 | 1 | 23 | 0 | 17 | 348.00 | 424.00 | 0 | 65.00 | 40.00 | 2662.00 | 0.00 | 1604.00 | 0.80 | 0.82 | 0.0 | 0.50 | 0.50 | 0.50 | 0.00 | 0.50 | 51 | 1 | 1483.0 | 1483.0 | 6 | 06-03 | 0 |
| 95 | CN0100002607 | 77.00 | 0.69 | 0.81 | 0.89 | 0.39 | 8 | 2 | 0 | 0 | 0 | 11 | 0 | 16 | 392.00 | 265.00 | 0 | 0.00 | 0.00 | 1479.00 | 0.00 | 1363.00 | 1.00 | 1.80 | 0.0 | 0.00 | 0.00 | 0.40 | 0.00 | 0.65 | 37 | 1 | 1449.2 | 1449.2 | 6 | 06-02 | 0 |
| 96 | CN0100002610 | 79.00 | 0.56 | 0.72 | 0.90 | 0.34 | 8 | 6 | 0 | 0 | 0 | 12 | 0 | 15 | 369.00 | 633.00 | 0 | 0.00 | 0.00 | 1353.00 | 0.00 | 1208.00 | 0.50 | 0.75 | 0.0 | 0.00 | 0.00 | 0.50 | 0.00 | 0.50 | 41 | 1 | 1381.2 | 1381.2 | 6 | 06-02 | 0 |
| 97 | CN0100002611 | 95.00 | 0.62 | 0.73 | 0.86 | 0.34 | 7 | 1 | 0 | 0 | 0 | 9 | 0 | 10 | 384.00 | 360.00 | 0 | 0.00 | 0.00 | 1121.00 | 0.00 | 942.00 | 0.90 | 1.00 | 0.0 | 0.00 | 0.00 | 0.50 | 0.00 | 0.60 | 27 | 1 | 1326.5 | 1326.5 | 6 | 06-02 | 0 |
| 98 | CN0100002612 | 55.50 | 0.82 | 0.32 | 0.31 | 0.07 | 83 | 1 | 0 | 0 | 3 | 13 | 0 | 4 | 4682.00 | 100.00 | 0 | 0.00 | 220.00 | 1592.00 | 0.00 | 484.00 | 1.00 | 0.50 | 0.0 | 0.00 | 0.80 | 0.50 | 0.00 | 0.50 | 104 | 1 | 1397.5 | 1397.5 | 6 | 06-06 | 0 |
| 99 | CN0100002617 | 107.00 | 0.68 | 0.00 | 0.00 | 0.00 | 15 | 4 | 0 | 1 | 0 | 25 | 0 | 3 | 1293.00 | 580.00 | 0 | 67.00 | 0.00 | 3106.00 | 0.00 | 291.00 | 1.00 | 0.65 | 0.0 | 0.50 | 0.00 | 0.50 | 0.00 | 0.50 | 48 | 1 | 1491.6 | 1491.6 | 6 | 06-01 | 0 |
| 100 | CN0100002618 | 167.50 | 0.55 | 0.95 | 0.96 | 0.86 | 4 | 1 | 0 | 0 | 0 | 4 | 0 | 19 | 162.00 | 45.00 | 0 | 0.00 | 0.00 | 429.00 | 0.00 | 3789.00 | 1.00 | 0.50 | 0.0 | 0.00 | 0.00 | 0.50 | 0.00 | 0.50 | 28 | 1 | 1431.5 | 1431.5 | 6 | 06-05 | 0 |
| 101 | CN0100002623 | 150.00 | 0.58 | 0.88 | 0.90 | 0.74 | 8 | 1 | 0 | 0 | 1 | 2 | 0 | 18 | 400.00 | 125.00 | 0 | 0.00 | 40.00 | 515.00 | 0.00 | 3139.00 | 0.75 | 0.70 | 0.0 | 0.00 | 0.80 | 0.45 | 0.00 | 0.50 | 30 | 1 | 1465.1 | 1465.1 | 6 | 06-05 | 0 |
| 102 | CN0100002660 | 120.00 | 0.00 | 0.00 | 0.00 | 0.00 | 19 | 13 | 0 | 0 | 3 | 10 | 0 | 0 | 1814.00 | 2040.00 | 0 | 0.00 | 266.00 | 1588.00 | 0.00 | 0.00 | 0.72 | 0.70 | 0.0 | 0.00 | 0.50 | 0.30 | 0.00 | 0.00 | 46 | 1 | 1333.7 | 1333.7 | 5 | 05-02 | 0 |
| 103 | CN0100002788 | 117.00 | 0.54 | 0.48 | 0.77 | 0.00 | 19 | 29 | 0 | 0 | 10 | 33 | 0 | 0 | 1870.00 | 4050.00 | 0 | 0.00 | 802.00 | 4754.00 | 0.00 | 0.00 | 0.70 | 0.70 | 0.0 | 0.00 | 0.30 | 0.30 | 0.00 | 0.00 | 91 | 1 | 1403.4 | 1403.4 | 5 | 05-02 | 0 |
| 104 | CN0100002796 | 112.50 | 0.53 | 0.00 | 0.00 | 0.00 | 18 | 19 | 0 | 0 | 15 | 17 | 0 | 0 | 1689.00 | 2814.00 | 0 | 0.00 | 1330.00 | 2417.00 | 0.00 | 0.00 | 0.60 | 0.50 | 0.0 | 0.00 | 0.30 | 0.25 | 0.00 | 0.00 | 71 | 1 | 1382.0 | 1382.0 | 5 | 05-02 | 0 |
| 105 | CN0100003913 | 80.00 | 0.35 | 1.00 | 0.77 | 0.01 | 0 | 1 | 0 | 0 | 24 | 51 | 0 | 1 | 0.00 | 22.00 | 0 | 0.00 | 1673.00 | 5474.00 | 0.00 | 56.00 | 0.00 | 0.35 | 0.0 | 0.00 | 0.35 | 0.35 | 0.00 | 0.00 | 77 | 1 | 1481.0 | 1481.0 | 10 | 10-01 | 1 |
| 106 | CN0100003919 | 70.00 | 0.35 | 1.00 | 1.00 | 0.39 | 0 | 0 | 0 | 0 | 0 | 11 | 0 | 6 | 0.00 | 0.00 | 0 | 0.00 | 0.00 | 820.00 | 0.00 | 526.00 | 0.00 | 0.00 | 0.0 | 0.00 | 0.00 | 0.35 | 0.00 | 0.35 | 17 | 1 | 1457.3 | 1457.3 | 10 | 10-02 | 1 |
| 107 | CN0100003923 | 67.00 | 0.37 | 1.00 | 0.65 | 0.05 | 0 | 0 | 0 | 0 | 38 | 39 | 3 | 3 | 0.00 | 0.00 | 0 | 0.00 | 2059.00 | 3693.00 | 100.00 | 231.00 | 0.00 | 0.00 | 0.0 | 0.00 | 0.35 | 0.35 | 0.35 | 0.35 | 84 | 1 | 1473.3 | 1473.3 | 10 | 10-01 | 1 |
| 108 | CN0100003924 | 78.00 | 0.35 | 1.00 | 0.90 | 0.34 | 0 | 0 | 0 | 0 | 13 | 41 | 0 | 23 | 0.00 | 0.00 | 0 | 0.00 | 647.00 | 3590.00 | 0.00 | 2153.00 | 0.00 | 0.00 | 0.0 | 0.00 | 0.35 | 0.35 | 0.00 | 0.35 | 77 | 1 | 1480.5 | 1480.5 | 10 | 10-02 | 1 |
| 109 | CN0100003952 | 76.50 | 0.00 | 0.00 | 0.00 | 0.00 | 0 | 0 | 0 | 0 | 25 | 47 | 0 | 3 | 0.00 | 0.00 | 0 | 0.00 | 58.00 | 3449.00 | 0.00 | 206.00 | 0.00 | 0.00 | 0.0 | 0.00 | 0.35 | 0.35 | 0.00 | 0.35 | 77 | 1 | 1466.4 | 1466.4 | 10 | 10-01 | 1 |
| 110 | CN0100003953 | 72.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0 | 0 | 0 | 0 | 25 | 62 | 0 | 35 | 0.00 | 0.00 | 0 | 0.00 | 710.00 | 6059.00 | 0.00 | 3019.00 | 0.00 | 0.00 | 0.0 | 0.00 | 0.35 | 0.35 | 0.00 | 0.35 | 122 | 1 | 1463.4 | 1463.4 | 10 | 10-02 | 1 |
| 111 | CN0100004959 | 74.00 | 0.35 | 1.00 | 0.89 | 0.02 | 0 | 0 | 0 | 0 | 5 | 21 | 0 | 1 | 0.00 | 0.00 | 0 | 0.00 | 244.00 | 1899.00 | 0.00 | 48.00 | 0.00 | 0.00 | 0.0 | 0.00 | 0.35 | 0.35 | 0.00 | 0.35 | 28 | 1 | 1203.5 | 1203.5 | 10 | 10-01 | 1 |
| 112 | CN0100004970 | 69.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0 | 0 | 0 | 0 | 7 | 30 | 0 | 25 | 0.00 | 0.00 | 0 | 0.00 | 339.00 | 2513.00 | 0.00 | 2103.00 | 0.00 | 0.00 | 0.0 | 0.00 | 0.35 | 0.35 | 0.00 | 0.35 | 62 | 1 | 1466.3 | 1466.3 | 10 | 10-02 | 1 |
| 113 | CN0100005013 | 73.00 | 0.69 | 0.74 | 0.92 | 0.28 | 5 | 4 | 1 | 0 | 0 | 11 | 0 | 7 | 126.00 | 437.00 | 85 | 0.00 | 0.00 | 1237.00 | 0.00 | 621.00 | 1.00 | 0.60 | 0.5 | 0.00 | 0.00 | 0.70 | 0.00 | 0.60 | 28 | 1 | 1404.5 | 1404.5 | 6 | 06-02 | 0 |
| 114 | CN0100005015 | 85.00 | 0.42 | 0.87 | 0.87 | 0.14 | 3 | 0 | 0 | 0 | 0 | 8 | 0 | 2 | 151.00 | 0.00 | 0 | 0.00 | 0.00 | 872.00 | 0.00 | 170.00 | 0.70 | 0.00 | 0.0 | 0.00 | 0.00 | 0.40 | 0.00 | 0.48 | 13 | 1 | 1213.3 | 1213.3 | 6 | 06-02 | 0 |
| 115 | CN0100005019 | 60.00 | 0.77 | 0.30 | 0.33 | 0.12 | 96 | 3 | 0 | 1 | 0 | 14 | 0 | 7 | 5767.00 | 154.00 | 0 | 100.00 | 0.00 | 1606.00 | 0.00 | 982.00 | 0.90 | 0.50 | 0.0 | 0.50 | 0.00 | 0.55 | 0.00 | 0.40 | 123 | 1 | 1409.4 | 1409.4 | 6 | 06-06 | 0 |
| 116 | CN0100005020 | 157.00 | 0.66 | 0.94 | 0.99 | 0.85 | 1 | 0 | 0 | 1 | 0 | 2 | 0 | 13 | 35.00 | 0.00 | 0 | 150.00 | 0.00 | 439.00 | 0.00 | 2468.00 | 1.60 | 0.00 | 0.0 | 0.80 | 0.00 | 0.60 | 0.00 | 0.70 | 17 | 1 | 1333.6 | 1333.6 | 6 | 06-05 | 0 |
| 117 | CN0100005258 | 69.00 | 2.92 | 0.85 | 0.03 | 0.00 | 1 | 1 | 0 | 0 | 9 | 0 | 0 | 0 | 110.00 | 29.00 | 0 | 0.00 | 753.00 | 0.00 | 0.00 | 0.00 | 0.50 | 0.80 | 0.0 | 0.00 | 1.00 | 0.00 | 0.00 | 0.00 | 12 | 1 | 1531.0 | 1531.0 | 1 | 01-01 | 1 |
| 118 | CN0100005259 | 59.00 | 0.00 | 0.00 | 0.00 | 0.00 | 2 | 0 | 0 | 0 | 42 | 2 | 0 | 0 | 120.00 | 0.00 | 0 | 0.00 | 2795.00 | 181.00 | 0.00 | 0.00 | 0.50 | 0.00 | 0.0 | 0.00 | 0.50 | 0.75 | 0.00 | 0.00 | 46 | 1 | 1536.3 | 1536.3 | 1 | 01-01 | 1 |
| 119 | CN0100005260 | 57.00 | 0.00 | 0.00 | 0.00 | 0.00 | 10 | 2 | 0 | 0 | 37 | 4 | 0 | 0 | 499.00 | 154.00 | 0 | 0.00 | 2383.00 | 299.00 | 0.00 | 0.00 | 0.60 | 0.60 | 0.0 | 0.00 | 0.50 | 0.65 | 0.00 | 0.00 | 53 | 1 | 1515.0 | 1515.0 | 1 | 01-01 | 1 |
| 120 | CN0100005261 | 67.00 | 0.00 | 0.00 | 0.00 | 0.00 | 7 | 0 | 0 | 0 | 32 | 6 | 0 | 0 | 544.00 | 0.00 | 0 | 0.00 | 1912.00 | 477.00 | 0.00 | 0.00 | 0.60 | 0.00 | 0.0 | 0.00 | 0.50 | 0.60 | 0.00 | 0.00 | 45 | 1 | 1440.4 | 1440.4 | 1 | 01-01 | 1 |
| 121 | CN0100005280 | 59.00 | 0.64 | 0.86 | 0.16 | 0.00 | 5 | 1 | 0 | 0 | 39 | 6 | 0 | 0 | 342.00 | 84.00 | 0 | 0.00 | 2275.00 | 397.00 | 0.00 | 0.00 | 0.90 | 1.50 | 0.0 | 0.00 | 0.50 | 0.45 | 0.00 | 0.00 | 51 | 1 | 1483.1 | 1483.1 | 1 | 01-01 | 1 |
| 122 | CN0100005281 | 70.00 | 0.60 | 0.80 | 0.09 | 0.00 | 8 | 2 | 0 | 0 | 31 | 2 | 0 | 0 | 561.00 | 143.00 | 0 | 0.00 | 2575.00 | 161.00 | 0.00 | 0.00 | 0.55 | 0.88 | 0.0 | 0.00 | 0.50 | 0.65 | 0.00 | 0.00 | 43 | 1 | 1512.9 | 1512.9 | 1 | 01-01 | 1 |
| 123 | CN0100010502 | 60.50 | 0.85 | 0.33 | 0.35 | 0.10 | 61 | 2 | 0 | 0 | 0 | 13 | 0 | 6 | 3715.00 | 132.00 | 0 | 0.00 | 0.00 | 1279.00 | 0.00 | 601.00 | 1.00 | 0.70 | 0.0 | 0.00 | 0.00 | 0.50 | 0.00 | 0.65 | 82 | 1 | 1317.8 | 1317.8 | 6 | 06-06 | 0 |
| 124 | CN0100010503 | 61.00 | 0.86 | 0.33 | 0.42 | 0.09 | 52 | 7 | 0 | 0 | 0 | 15 | 0 | 4 | 3049.00 | 504.00 | 0 | 0.00 | 0.00 | 1264.00 | 0.00 | 459.00 | 1.00 | 0.50 | 0.0 | 0.00 | 0.00 | 0.50 | 0.00 | 1.00 | 78 | 1 | 1358.1 | 1358.1 | 6 | 06-06 | 0 |
| 125 | CN0100011408 | 63.00 | 0.53 | 0.82 | 1.00 | 0.00 | 0 | 17 | 0 | 0 | 0 | 76 | 0 | 0 | 0.00 | 1351.00 | 0 | 0.00 | 0.00 | 6241.00 | 0.00 | 0.00 | 0.00 | 0.50 | 0.0 | 0.00 | 0.00 | 0.50 | 0.00 | 0.00 | 93 | 1 | 0.0 | 0.0 | 12 | 12-01 | 1 |
| 126 | CN0100011411 | 84.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0 | 8 | 0 | 0 | 0 | 60 | 0 | 0 | 0.00 | 513.00 | 0 | 0.00 | 0.00 | 4922.00 | 0.00 | 0.00 | 0.00 | 0.50 | 0.0 | 0.00 | 0.00 | 0.50 | 0.00 | 0.00 | 68 | 1 | 0.0 | 0.0 | 12 | 12-01 | 1 |
| 128 | CN0100011500 | 130.12 | 0.49 | 0.93 | 0.82 | 0.15 | 0 | 0 | 0 | 0 | 14 | 21 | 0 | 5 | 0.00 | 0.00 | 0 | 0.00 | 1052.27 | 3741.67 | 0.00 | 911.88 | 0.00 | 0.00 | 0.0 | 0.00 | 0.32 | 0.30 | 0.00 | 0.30 | 44 | 1 | 1440.3 | 1440.3 | 4 | 04-06 | 0 |
| 129 | CN0100013261 | 64.50 | 0.89 | 0.00 | 0.00 | 0.00 | 90 | 5 | 0 | 0 | 0 | 14 | 0 | 6 | 5738.00 | 925.00 | 0 | 0.00 | 0.00 | 1611.00 | 0.00 | 389.00 | 1.00 | 0.55 | 0.0 | 0.00 | 0.00 | 0.65 | 0.00 | 0.60 | 117 | 1 | 1475.3 | 1475.3 | 6 | 06-06 | 0 |
Clustering
a <- scale(agcs[model_columns])
d <- dist(a, method = "euclidean")
clsize <- 80
agcs$cluster.nn.min <-
fixed_size_clustering_nearest_neighbor(d, size = clsize, method = "min")
agcs$cluster.hc.wardD2 <-
fixed_size_clustering_hclust(d, size = clsize, method = "ward.D2")
agcs$cluster.km.rst.rng <-
fixed_size_clustering_kmeans(a, size = clsize, method = "range")
agcs$cluster.km.std <-
kmeans(a, ceiling(nrow(a) / clsize))$cluster
write.csv(
agcs,
file = find_git_root_file(
"export",
paste0(format(Sys.Date(), "%Y%m%d"), "_agcs_per_cluster.csv")
),
row.names = FALSE
)
cols <- viridisLite::viridis(max(agcs$cluster.nn.min))
library("pvclust")
pv <- pvclust(
t(a), method.hclust = "ward.D2", method.dist = "euclidean",
nboot = 100,
quiet = TRUE
)
pvd <- as.dendrogram(pv)
par(mar = c(12, 2, 2, 1))
plot(pvd)
text(pv)
cls <- cbind(
nn.min = agcs$cluster.nn.min,
km.rst.rng = agcs$cluster.km.rst.rng,
km.std = agcs$cluster.km.std,
hc.wardD2 = agcs$cluster.hc.wardD2
)
cls[] <- cols[cls]
colored_bars(cls, pvd)
colored_bars(
cbind(
center = agcs$center,
or.id = match(agcs$or, unique(agcs$or))
),
pvd, y_shift = -4.5
)
wss <- sapply(
list(
nn.min = agcs$cluster.nn.min,
km.rst.rng = agcs$cluster.km.rst.rng,
km.std = agcs$cluster.km.std,
hc.wardD2 = agcs$cluster.hc.wardD2
),
within_cluster_sum_of_squares, x = a
)
tss <- total_sum_of_squares(a)
col <- seq_len(ncol(wss))
barplot(
t(wss), col = col, beside = TRUE,
main = "Within cluster sum of squares"
)
legend("topright", legend = colnames(wss), col = col, pch = 15)
barplot(
1 - colSums(wss) / tss, col = col, horiz = TRUE,
main = "Between/Total sum of squares"
)
legend(
"bottomright",
legend = colnames(wss),
col = col, pch = 15,
bty = "n"
)
Lineare Regression
Behalte nur Filter mit 80 Filtern pro Gruppe.
keep <-
agcs$cluster.nn.min %in% which(table(agcs$cluster.nn.min) == clsize)
table(keep)## keep
## FALSE TRUE
## 8 80##
## Call:
## lm(formula = weight ~ 0 + n.cases.lama.nonlap.tiva + n.cases.tube.nonlap.tiva +
## n.cases.tube.lap.tiva + n.cases.lama.nonlap.inha + n.cases.tube.nonlap.inha +
## n.cases.tube.lap.inha + sum.dura.lama.nonlap.tiva + sum.dura.tube.nonlap.tiva +
## sum.dura.tube.lap.tiva + sum.dura.lama.nonlap.inha + sum.dura.tube.nonlap.inha +
## sum.dura.tube.lap.inha + med.flow.lama.nonlap.tiva + med.flow.tube.nonlap.tiva +
## med.flow.tube.lap.tiva + med.flow.lama.nonlap.inha + med.flow.tube.nonlap.inha +
## med.flow.tube.lap.inha + water.trap, data = agcs[keep, ])
##
## Residuals:
## Min 1Q Median 3Q Max
## -770.13 -127.25 41.39 210.67 870.79
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## n.cases.lama.nonlap.tiva -7.702e+00 1.881e+01 -0.410 0.68356
## n.cases.tube.nonlap.tiva -6.633e+01 2.115e+01 -3.137 0.00263 **
## n.cases.tube.lap.tiva 5.965e+02 6.407e+02 0.931 0.35550
## n.cases.lama.nonlap.inha -5.534e+00 1.111e+01 -0.498 0.62010
## n.cases.tube.nonlap.inha 5.893e+00 9.080e+00 0.649 0.51879
## n.cases.tube.lap.inha 8.950e+00 1.547e+01 0.579 0.56501
## sum.dura.lama.nonlap.tiva 1.340e-01 3.112e-01 0.431 0.66816
## sum.dura.tube.nonlap.tiva 5.607e-01 1.863e-01 3.009 0.00381 **
## sum.dura.tube.lap.tiva 1.077e-01 2.901e+00 0.037 0.97050
## sum.dura.lama.nonlap.inha 2.817e-01 1.748e-01 1.611 0.11237
## sum.dura.tube.nonlap.inha -7.355e-03 8.046e-02 -0.091 0.92747
## sum.dura.tube.lap.inha 1.999e-02 1.362e-01 0.147 0.88375
## med.flow.lama.nonlap.tiva 2.656e+02 1.121e+02 2.368 0.02107 *
## med.flow.tube.nonlap.tiva 1.799e+02 1.186e+02 1.517 0.13455
## med.flow.tube.lap.tiva -1.084e+03 1.077e+03 -1.007 0.31780
## med.flow.lama.nonlap.inha 3.739e+02 1.676e+02 2.231 0.02937 *
## med.flow.tube.nonlap.inha 4.834e+02 2.998e+02 1.613 0.11200
## med.flow.tube.lap.inha 8.984e+02 2.848e+02 3.155 0.00250 **
## water.trap 2.485e+02 1.331e+02 1.867 0.06674 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 356.9 on 61 degrees of freedom
## Multiple R-squared: 0.9503, Adjusted R-squared: 0.9348
## F-statistic: 61.39 on 19 and 61 DF, p-value: < 2.2e-16Penalized Regression
y <- agcs[keep, "weight"]
X <- model.matrix(
weight ~ 0 +
n.cases.lama.nonlap.tiva +
n.cases.tube.nonlap.tiva +
n.cases.tube.lap.tiva +
n.cases.lama.nonlap.inha +
n.cases.tube.nonlap.inha +
n.cases.tube.lap.inha +
sum.dura.lama.nonlap.tiva +
sum.dura.tube.nonlap.tiva +
sum.dura.tube.lap.tiva +
sum.dura.lama.nonlap.inha +
sum.dura.tube.nonlap.inha +
sum.dura.tube.lap.inha +
med.flow.lama.nonlap.tiva +
med.flow.tube.nonlap.tiva +
med.flow.tube.lap.tiva +
med.flow.lama.nonlap.inha +
med.flow.tube.nonlap.inha +
med.flow.tube.lap.inha +
water.trap,
data = agcs[keep, ]
)
## TODO: replace y with measured weight and drop `jitter` call (just used to
## avoid error about constant y)
#Y <- jitter(y)
Y <- y
## TODO: increase nrepcv and nfolds for final calculations
## number of repeated cv for model estimation
nrepcv <- 2
## number of cv folds for model estimation
nfolds <- 5
## number of repeated cv for mse estimation (authors of nested_cv suggest at
## least 50)
mse.nrepcv <- 5
## number of cv folds for mse estimation
mse.nfolds <- 5
## percentage of training data
ptrain <- 0.8
## helper functions
se_loss_rcv.glmnet <- function(y1, y2, funcs_params = NULL) {
(y1 - y2)^2
}
fitter_rcv.glmnet <- function(X, Y, idx = seq_len(nrow(X)), funcs_params = NULL) {
rcv.glmnet(
X[idx, ], Y[idx],
lambda = funcs_params$lambda,
alpha = funcs_params$alpha,
intercept = funcs_params$intercept,
nfolds = funcs_params$nfolds,
nrepcv = funcs_params$nrepcv
)
}
predictor_rcv.glmnet <- function(fit, X_new, funcs_params = NULL) {
predict(fit, X_new, s = funcs_params$s)
}
funcs_rcv.glmnet <- list(
fitter = fitter_rcv.glmnet,
predictor = predictor_rcv.glmnet,
loss = se_loss_rcv.glmnet
)
params <- list(
alpha = 1,
s = "lambda.1se",
intercept = FALSE,
nfolds = nfolds,
nrepcv = nrepcv
)
set.seed(1)
nr <- nrow(X)
ntrain <- ceiling(nr * ptrain)
train_idx <- sample(seq_len(nr), ntrain, replace = FALSE)
test_idx <- setdiff(seq_len(nr), train_idx)
X_train <- X[train_idx, ]
Y_train <- Y[train_idx]
## fit once to keep lambda/best lambda fixed
fit <- funcs_rcv.glmnet$fitter(X_train, Y_train, funcs_params = params)
params$lambda <- fit$lambda
params$lambda.min <- fit$lambda.min
out <- nested_cv(
X_train, Y_train,
funcs = funcs_rcv.glmnet,
n_folds = mse.nfolds,
reps = mse.nrepcv,
n_cores = parallel::detectCores(),
funcs_params = params,
alpha = 0.05
)
out[["ho_err"]] <- mean(funcs_rcv.glmnet$loss(
funcs_rcv.glmnet$predictor(fit, X[test_idx, ], funcs_params = params),
Y[test_idx],
funcs_params = params
))
out## $sd_infl
## [1] 1.955672
##
## $err_hat
## [1] 171072.8
##
## $ci_lo
## [1] -16498.46
##
## $ci_hi
## [1] 358644
##
## $raw_mean
## [1] 252121.1
##
## $bias_est
## [1] 81048.3
##
## $sd
## [1] 391482.4
##
## $running_sd_infl
## [1] 1.722672 1.335926 1.543523 1.578283 1.955672
##
## $ho_err
## [1] 221765.6# RMSE
sqrt(c(out$err_hat, out$ho_err))## [1] 413.6095 470.9200knitr::kable(
cbind(
as.matrix(coef(fit, s = "lambda.1se")),
as.matrix(coef(fit, s = "lambda.min"))[, 1]
),
col.names = c("variable", "s, lambda.1se", "s, lambda.min")
)| variable | s, lambda.1se | s, lambda.min |
|---|---|---|
| (Intercept) | 0.0000000 | 0.0000000 |
| n.cases.lama.nonlap.tiva | 0.0000000 | 0.0000000 |
| n.cases.tube.nonlap.tiva | 0.0000000 | -53.7992204 |
| n.cases.tube.lap.tiva | 0.0000000 | 81.0423025 |
| n.cases.lama.nonlap.inha | 0.0000000 | -1.1874496 |
| n.cases.tube.nonlap.inha | 0.0000000 | 1.0580854 |
| n.cases.tube.lap.inha | 13.0482228 | 14.8578266 |
| sum.dura.lama.nonlap.tiva | 0.0232925 | 0.0144212 |
| sum.dura.tube.nonlap.tiva | 0.0276881 | 0.5317458 |
| sum.dura.tube.lap.tiva | 0.0000000 | -0.5383752 |
| sum.dura.lama.nonlap.inha | 0.1639116 | 0.3264877 |
| sum.dura.tube.nonlap.inha | 0.0133769 | 0.0000000 |
| sum.dura.tube.lap.inha | 0.0000000 | 0.0000000 |
| med.flow.lama.nonlap.tiva | 227.3882037 | 294.3472264 |
| med.flow.tube.nonlap.tiva | 0.0000000 | 114.9042264 |
| med.flow.tube.lap.tiva | 0.0000000 | -186.9612930 |
| med.flow.lama.nonlap.inha | 453.6151844 | 452.7160133 |
| med.flow.tube.nonlap.inha | 1089.9039942 | 0.0000000 |
| med.flow.tube.lap.inha | 318.1987866 | 1215.0468646 |
| water.trap | 0.0000000 | 254.9845575 |
plot(fit)
plot(fit, "path")