Greetings. I have used semipar function of Stata with graph option for 426,000 observations to estimate semi-parametric regression of dependent variable on several independent variables in linear form and one variable as a flexible functional form to be considered as non-parametric variable. I gave the command 48 hours ago, however, the command is still running. I do not know when I will get my output. Alternatively, i tried the same regression for a sub-sample of 1,000 observations but i have not got the output within 30 minutes, then i canceled the operation. For reference, I have shared my command and data sample below. Would you please help me out by identifying my mistake or suggesting efficient way to handle this problem? Thank you.
Code:
semipar mflow alpha mflowL logTNA logAGE EXPR REAR, nonpar(FSB) xtitle(FSB) ci
Code:
* Example generated by -dataex-. To install: ssc install dataex
clear
input float(mflow alpha mflowL logTNA logAGE) double EXPR byte REAR float FSB
.06142427 -.00007701437 .09345506 5.805526 1.2039728 .007 1 -.0005415289
.02658373 .005997835 -.04395232 5.362667 1.2039728 .0079 1 .005259412
.00018048484 .000999924 .023868304 4.417635 1.446919 0 1 -.0016591768
-.035596263 .0016930813 .0026768625 3.795399 2.957511 .0069 1 -.0020691568
.08475412 -.000187979 .06142427 5.895565 1.2286655 .007 1 -.0011507465
.05474074 .008758709 .02658373 5.435581 1.2286655 .0079 1 .004928627
.01248491 .0015635238 -.035596263 3.825201 2.961831 .0069 1 -.0044297883
.06776663 .001072005 .00018048484 4.4886365 1.466337 0 1 -.0012998166
.01606508 .0014608257 .01248491 3.8657696 2.966132 .0069 1 -.002229583
.030364953 .007016675 .05474074 5.483921 1.252763 .0079 1 .0005581158
.08002505 .0009161719 .06776663 4.5736794 1.4853852 0 1 -.001498271
.1008181 -.0004140712 .08475412 6.009427 1.252763 .007 1 -.0009622335
.04361444 .01112596 .030364953 5.5418 1.2762934 .0079 1 .00017001225
.0813513 .0008834972 .08002505 4.6577625 1.5040774 0 1 -.0012104682
.010070225 .0020960646 .01606508 3.895548 2.9704144 .0069 1 -.0006541223
.10232854 -.0007423428 .1008181 6.124427 1.2762934 .007 1 .0005680091
.11509213 .0010447002 .0813513 4.772378 1.5224266 0 1 -.0014547526
.10861416 -.0009437219 .10232854 6.236493 1.299283 .007 1 .001206447
.035726815 .014936568 .04361444 5.598429 1.299283 .0079 1 -.0000724135
.002450603 .0022881522 .010070225 3.908898 2.974679 .0069 1 -.000651091
.02406323 .018815147 .035726815 5.631749 1.321756 .0079 1 -.000399879
.0002104824 .003690503 .002450603 3.918303 2.978925 .0069 1 -.0009268375
.09328988 -.00017967848 .10861416 6.335515 1.321756 .007 1 .00128309
-.022381427 .0010966233 .11509213 4.7570324 1.540445 0 1 -.0014206193
.0008084829 .002905097 .0002104824 3.954546 2.9831536 .0069 1 -.0009438918
-.005911467 .001314592 -.022381427 4.7613187 1.5581446 0 1 -.001390465
.0005135556 .01891317 .02406323 5.651362 1.3437347 .0079 1 -.0004524317
.0797721 -5.512099e-06 .09328988 6.438484 1.3437347 .007 1 .0013454867
-.1496443 .0009976532 -.005911467 4.6021657 1.5755364 0 1 -.0012228353
-.0030045186 .0031624115 .0008084829 3.9402995 2.987364 .0068 1 -.0003094229
.1498355 -.00026522044 .0797721 6.561479 1.365241 .009 1 .002032796
.05693629 .0210311 .0005135556 5.724588 1.365241 .0094 1 -.001676965
.12017477 -.0009618956 .1498355 6.680723 1.3862944 .009 1 .00027987495
.15430064 .0032259275 -.0030045186 4.0898175 2.991557 .0068 1 -.0013707738
-.1023339 .0011437794 -.1496443 4.497585 1.5926307 0 1 -.0010388659
.021618327 .017394518 .05693629 5.761507 1.3862944 .0094 1 -.0038289665
-.006155239 .002595417 .15430064 4.078334 2.995732 .0068 1 -.0019615197
.021909716 .0009664675 -.1023339 4.5196123 1.609438 0 1 -.001289533
.07571987 -.0010825517 .12017477 6.748365 1.4069136 .009 1 .000951598
.04003801 .013780753 .021618327 5.80599 1.4069136 .0094 1 -.0042301677
.007516535 .0022012626 -.006155239 4.092309 2.99989 .0068 1 -.0025436056
-.0030387016 .0006912753 .021909716 4.52396 1.6259673 0 1 -.0018465634
.19640027 .011309516 .04003801 5.989282 1.4271163 .0094 1 -.005588527
.06781927 -.0011145149 .07571987 6.820099 1.4271163 .009 1 .00024893033
-.006190598 .0008545409 -.0030387016 4.522875 1.6422276 0 1 -.0009915882
-.00006084931 .0013775495 -.005789 5.001931 3.1098046 .0124 1 -.009085847
.06344786 -.0011151778 .06781927 6.897247 1.446919 .009 1 .00015062357
.00027926321 .0015498564 .007516535 4.115127 3.004031 .0068 1 -.002954414
-.11934887 .0101219 .19640027 5.874001 1.446919 .0094 1 -.006163663
-.03606929 .0009498876 -.006190598 4.4897594 1.658228 0 1 -.001352241
-.014404282 .00004046849 .002966798 6.489283 .9162908 .004 1 -.0016162507
-.00804203 .001571646 -.00006084931 5.005958 3.1135154 .0124 1 -.0083020525
.02720734 .001945871 .004736708 3.7395725 .9162908 .0033 1 -.002140493
.0442791 -.0012927772 .06344786 6.954967 1.466337 .009 1 -.00007768975
.03870124 .011073073 -.11934887 5.921289 1.466337 .0094 1 -.006003893
-.0019808675 .001604684 .00027926321 4.1314316 3.008155 .0068 1 -.0020233255
.0027059496 .0019753443 -.0019808675 4.1669908 3.0122616 .0068 1 -.001682181
.0688294 .000771197 -.03606929 4.5591264 1.6739764 0 1 -.001737805
.03265522 .010504276 .03870124 5.974219 1.4853852 .0094 1 -.004340083
-.0001340596 .0011294313 -.00804203 5.028475 3.117212 .0124 1 -.00814419
.07761426 .00006282002 -.014404282 6.567595 .9490805 .004 1 -.00153382
.2501607 .0021982067 .02720734 3.980485 .9490805 .0033 1 -.0020693238
.06638545 -.001253826 .0442791 7.04108 1.4853852 .009 1 -.0004652972
.03656212 .010578724 .03265522 6.025277 1.5040774 .0094 1 -.004802327
.002739633 .0023882026 .0027059496 4.17841 3.0163515 .0068 1 .0007547074
-.006602606 .0014091296 -.0001340596 5.031744 3.1208954 .0124 1 -.007417512
-.25867513 .000032680757 .07761426 6.126347 .9808293 .004 1 -.0013472944
-.10021084 .0007533834 .0688294 4.4601445 1.6894805 0 1 -.002370697
.00838021 .002551545 .2501607 3.996456 .9808293 .0033 1 -.0014210194
.05404568 -.0008240653 .06638545 7.102348 1.5040774 .009 1 .0011466013
-.02436311 .00082957 -.10021084 4.441474 1.704748 0 1 -.002380928
.2471334 -.000015242078 -.25867513 6.349926 1.011601 .004 1 -.001354269
.004450624 .0022587993 .00838021 4.020106 1.011601 .0033 1 -.0014581778
.05190275 -.0008692344 .05404568 7.166162 1.5224266 .009 1 .0011411711
.04491969 .0107694 .03656212 6.081511 1.5224266 .0094 1 -.0046173367
-.01415376 .0021733474 .002739633 4.175617 3.020425 .0068 1 .0006252178
-.015732674 .0016351067 -.006602606 5.025852 3.124565 .0124 1 -.0074384
.7812297 .000015771011 .2471334 6.928217 1.0414538 .004 1 -.001261789
-.01049875 .001428472 -.015732674 4.997212 3.1282215 .0124 1 -.007963448
-.08099536 .0018958178 -.01415376 4.074805 3.024482 .0068 1 -.000020186097
.03917046 -.0007660271 .05190275 7.190769 1.540445 .009 1 .001305357
-.04821699 .010680643 .04491969 6.014485 1.540445 .0094 1 -.00557392
-.065162584 .001205248 -.0227588 2.580444 .9162908 .002 1 -.00052613067
-.04136892 .0005180608 -.03039349 2.482654 .9162908 .023 1 -.003348782
-.07791165 .0009104254 -.02436311 4.352855 1.719786 0 1 -.0022730334
.0334033 .002722006 .004450624 4.036009 1.0414538 .0033 1 -.0005900306
-.02422193 -.0004587063 -.04136892 2.4550486 .9490805 .023 1 -.004382292
.014255114 -.0005865431 .03917046 7.200355 1.5581446 .009 1 -.0002275679
.04469506 .005719021 -.04821699 6.078034 1.5581446 .0094 1 -.008123649
-.25867513 -.0000416555 .7812297 6.395076 1.0704415 .004 1 -.0013842816
-.0956372 .0011813188 -.065162584 2.4767065 .9490805 .002 1 -.0019714439
.003021754 .0015701263 -.08099536 4.0757394 3.028522 .0068 1 -.0010070017
-.0034670064 -.0002723711 -.07791165 4.3463993 1.734601 0 1 -.0034285414
-.0040416485 .00033518884 -.01049875 4.998563 3.131864 .0124 1 -.008548275
.02394063 .0013275605 .0334033 4.0552573 1.0704415 .0033 1 -.00137038
-.01041108 .0012512715 .003021754 4.0816307 3.032546 .0068 1 -.0018487276
-.015636599 .0006142295 -.0040416485 5.005958 3.135494 .0124 1 -.0084052365
.13667588 -.00012694816 -.25867513 6.525782 1.0986123 .004 1 -.0014079948
.05260683 -.0007623637 -.0034670064 4.405499 1.7492 0 1 -.003968108
-.005927357 -.000978984 -.02422193 2.458306 .9808293 .023 1 -.005293334
end
0 Response to Semi-parametric regression with figure for large dataset
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