Dear All, Given the following data (taken from https://cran.r-project.org/web/packa...gnettes/rq.pdf)
How can I draw graph like this?
We can run the following regressions:
But, how to graph them in one figure? Thanks.
Code:
* Example generated by -dataex-. To install: ssc install dataex clear input int id float(income foodexp) 1 420.15765 255.83943 2 541.4117 310.9587 3 901.1575 485.68 4 639.0802 402.9973 5 750.8756 495.5608 6 945.799 633.7978 7 829.3979 630.7566 8 979.1649 700.4409 9 1309.879 830.9586 10 1492.3988 815.3602 11 502.839 338.0014 12 616.7169 412.3613 13 790.9225 520.0006 14 555.87866 452.4015 15 713.4412 512.72003 16 838.7561 658.8395 17 535.07666 392.5995 18 596.4408 443.5586 19 924.5619 640.1164 20 487.7583 333.8394 21 692.6397 466.9583 22 997.877 543.3969 23 506.9995 317.71985 24 654.1587 424.3209 25 933.9193 518.9617 26 433.6813 338.0014 27 587.5962 419.6412 28 896.4746 476.32 29 454.4782 386.3602 30 584.9989 423.27835 31 800.799 503.3572 32 502.4369 354.6389 33 713.5197 497.3182 34 906.0006 588.5195 35 880.5969 654.5972 36 796.8289 550.7274 37 854.879 528.37695 38 1167.3716 640.4813 39 523.80005 401.3203 40 670.7792 435.999 41 377.0584 276.5606 42 851.543 588.3488 43 1121.0938 664.1978 44 625.5179 444.8602 45 805.5377 462.8995 46 558.5812 377.7792 47 884.4005 553.15045 48 1257.499 810.8962 49 2051.179 1067.9541 50 1466.333 1049.8788 51 730.0989 522.70123 52 800.799 572.0807 53 1245.6964 907.397 54 1201.0002 811.5776 55 634.4002 427.7975 56 956.2314 649.9985 57 1148.6011 860.6002 58 1768.8236 1143.4211 59 2822.533 2032.6792 60 922.3549 590.61835 61 2293.192 1570.391 62 627.4726 483.48 63 889.9809 600.4804 64 1162.2 696.2021 65 1197.0793 774.7962 66 530.7972 390.5984 67 1142.1526 612.5619 68 1088.0039 708.7621 69 484.6612 296.9192 70 1536.02 1071.4626 71 678.8974 496.5976 72 671.8802 503.3974 73 690.4683 357.6411 74 860.6948 430.3376 75 873.3095 624.699 76 894.4598 582.54126 77 1148.647 580.22156 78 926.8762 543.88074 79 839.0414 588.6372 80 829.4974 627.9999 81 1264.0043 712.1012 82 1937.977 968.395 83 698.8317 482.5816 84 920.4199 593.1694 85 1897.571 1033.5658 86 891.6824 693.6794 87 889.6783 693.6794 88 1221.4818 761.2791 89 544.5991 361.3981 90 1031.4491 628.4522 91 1462.9497 771.4485 92 830.4353 757.1187 93 975.0414 821.597 94 1337.9983 1022.3202 95 867.6427 679.4407 96 725.7459 538.74915 97 989.0056 679.9981 98 1525.0005 977.0033 99 672.196 561.2015 100 923.3977 728.3997 101 472.3215 372.3186 102 590.7601 361.521 103 940.9218 517.9196 104 643.3571 459.8177 105 2551.6616 863.9199 106 1795.3226 831.4407 107 1165.7734 534.76105 108 815.6212 392.0502 109 1264.2065 934.9752 110 1095.4056 813.3081 111 447.4478 263.71 112 1178.9741 769.0839 113 975.8023 630.5863 114 1017.8522 645.9874 115 423.8798 319.5584 116 558.77673 348.4518 117 943.2487 614.5068 118 1348.3003 662.0096 119 2340.6174 1504.3707 120 587.17914 406.218 121 1540.974 692.1689 122 1115.848 588.137 123 1044.6843 511.2609 124 1389.793 700.56 125 2497.786 1301.145 126 1585.381 879.066 127 1862.044 912.8851 128 2008.8546 1509.781 129 697.3099 484.06055 130 571.2518 399.6703 131 598.3465 444.1001 132 461.0977 248.8101 133 977.1107 527.80133 134 883.9849 500.63135 135 718.3594 436.8107 136 543.89703 374.799 137 1587.348 726.3922 138 4957.813 1827.2 139 969.6838 523.4911 140 419.998 334.9998 141 561.99896 473.2009 142 689.5988 581.20294 143 1398.5203 929.754 144 820.8168 591.1974 145 875.1716 637.5483 146 1392.45 674.9509 147 1256.3174 776.7589 148 1362.859 959.517 149 1999.2552 1250.9644 150 1209.473 737.8201 151 1125.0356 810.6772 152 1827.401 983.0009 153 1014.154 708.8969 154 880.3944 633.12 155 2432.391 1424.8047 156 1177.8547 830.9586 157 1222.594 925.5795 158 1519.581 1162.0024 159 687.6638 383.458 160 953.1192 621.1173 161 953.1192 621.1173 162 953.1192 621.1173 163 939.0418 548.6002 164 1283.4025 745.2353 165 1511.579 837.8005 166 1342.582 795.3403 167 511.798 418.5976 168 689.7988 508.7975 169 1532.3074 883.278 170 1056.0808 742.5276 171 387.3195 242.3202 172 387.3195 242.3202 173 410.9987 266.00098 174 832.7554 614.7588 175 614.9986 385.3184 176 887.4658 515.62 177 1024.8176 708.4787 178 1006.4354 734.2357 179 726 433.001 180 494.4174 327.4188 181 748.6414 429.03995 182 987.6417 619.6408 183 788.0961 400.799 184 831.7983 620.8007 185 1139.4945 819.9965 186 507.5169 360.878 187 576.1972 395.7608 188 696.5991 442.0001 189 650.818 404.0384 190 949.5802 670.7993 191 497.1193 297.57016 192 570.1674 353.4882 193 724.7306 383.9376 194 408.3399 284.8008 195 638.6713 431.1 196 1225.789 801.3517 197 715.3701 448.4513 198 800.4708 577.9111 199 975.5974 570.521 200 1613.7566 865.3206 201 608.5019 444.5578 202 958.6634 680.4198 203 835.9426 576.2779 204 873.7375 631.7982 205 951.4432 608.64185 206 473.0022 300.9999 207 601.00305 377.9984 208 713.9979 397.0015 209 829.2983 588.5195 210 959.7953 681.7616 211 1212.9613 807.3603 212 958.8743 696.8011 213 1129.4431 811.1962 214 1943.042 1305.72 215 539.6388 442.0001 216 463.599 353.6013 217 562.64 468.0008 218 736.7584 526.7573 219 1415.446 890.239 220 2208.7898 1318.8032 221 636.0009 331.00055 222 759.401 416.4015 223 1078.8383 596.8406 224 499.751 408.4992 225 1020.0225 775.0209 226 1595.161 1138.162 227 776.5958 485.5198 228 1230.9236 772.7612 229 1807.952 993.963 230 415.4407 305.439 231 440.5174 306.5191 232 541.2006 299.19934 233 581.35986 468.0008 234 743.0773 522.6019 235 1057.6768 750.3202 end
We can run the following regressions:
Code:
// OLS reg foodexp income // Quantile = 0.05 qreg foodexp income, q(0.05) // Quantile = 0.1 qreg foodexp income, q(0.1) // Quantile = 0.25 qreg foodexp income, q(0.25) // Quantile = 0.5 (Median) qreg foodexp income, q(0.5) // Quantile = 0.75 qreg foodexp income, q(0.75) // Quantile = 0.95 qreg foodexp income, q(0.95)
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