使用sas做一个面板数据估计威布尔方程的系数

这是原始数据
data so2;
   input year state income so2;
datalines;
1997 1 1.431168436 0.017002177
1998 1 1.672779233 0.015482905
1999 1 1.984630128 0.012861893
2000 1 2.245965659 0.010595586
2001 1 2.5523 0.009132972
2002 1 2.8449 0.008472663
2003 1 3.2061 0.007828344
2004 1 3.7058 0.008372405
2005 1 4.544369288 0.006827048
2006 1 5.0467 0.005945604
2007 1 5.8204 0.005077106
1997 2 1.302176483 0.024652991
1998 2 1.399423328 0.020930721
1999 2 1.597633397 0.015825756
2000 2 1.799319504 0.024157343
2001 2 2.015443593 0.019775797
2002 2 2.238 0.019937736
2003 2 2.65320369 0.022759913
2004 2 3.155 0.019628906
2005 2 3.57831885 0.023106424
2006 2 4.1163 0.021581395
2007 2 4.6122 0.020159193
1997 3 0.606043854 0.015462406
1998 3 0.648605803 0.018449475
1999 3 0.693196369 0.016881857
2000 3 0.766275771 0.016809001
2001 3 0.8362 0.01635986
2002 3 0.9115 0.01564003
2003 3 1.0513239 0.017652184
2004 3 1.2918 0.01784403
2005 3 1.478225972 0.018698
2006 3 1.6962 0.019222963
2007 3 1.9877 0.018643468
1997 4 0.471296252 0.021944763
1998 4 0.506236257 0.034689439
1999 4 0.472653015 0.029096473
2000 4 0.513705073 0.02737886
2001 4 0.546 0.027568765
2002 4 0.6146 0.027535549
2003 4 0.7435 0.031178292
2004 4 0.915 0.032773613
2005 4 1.2495 0.035767511
2006 4 1.4123 0.034874074
2007 4 1.6945 0.032964174
1997 5 0.470980611 0.022854815
1998 5 0.510043583 0.024243198
1999 5 0.535015187 0.022092125
2000 5 0.58717938 0.021309301
2001 5 0.64625219 0.02040833
2002 5 0.7241 0.02349731
2003 5 0.897464587 0.047815314
2004 5 1.1305 0.043372483
2005 5 1.633081867 0.054316848
2006 5 2.0053 0.05773884
2007 5 2.5393 0.053357609
1997 6 0.843478903 0.020242315
1998 6 0.934331236 0.018081501
1999 6 1.00862911 0.017349437
2000 6 1.122640058 0.016651062
2001 6 1.204086124 0.014486171
2002 6 1.2986 0.013633476
2003 6 1.425781473 0.015136936
2004 6 1.6297 0.015390088
2005 6 1.898320126 0.022767117
2006 6 2.1788 0.024280028
2007 6 2.5729 0.024829824
1997 7 0.55064635 0.007350989
1998 7 0.589360878 0.008005106
1999 7 0.634083167 0.007901467
2000 7 0.68474027 0.007393255
2001 7 0.764001188 0.007083835
2002 7 0.8334 0.00693405
2003 7 0.9338 0.006969486
2004 7 1.0932 0.007973422
2005 7 1.3348 0.011340206
2006 7 1.572 0.012339332
2007 7 1.9383 0.01232844
1997 8 0.722104377 0.005982858
1998 8 0.752186866 0.005876915
1999 8 0.766003966 0.005663871
2000 8 0.856165285 0.006008946
2001 8 0.934891048 0.005745211
2002 8 1.0184 0.005594597
2003 8 1.16151 0.007478532
2004 8 1.3897 0.007728583
2005 8 1.443405615 0.011282723
2006 8 1.6195 0.011509286
2007 8 1.8478 0.011517226
1997 9 2.289259948 0.027518668
1998 9 2.546716346 0.026699044
1999 9 3.080474864 0.021089891
2000 9 3.454697961 0.019522342
2001 9 3.7382 0.01859114
2002 9 4.0646 0.019995077
2003 9 4.6718 0.018445996
2004 9 5.5307 0.020091848
2005 9 5.1474 0.021091114
2006 9 5.7695 0.020606061
2007 9 6.6367 0.019613358
1997 10 0.935369124 0.013964368
1998 10 1.005398872 0.016927625
1999 10 1.066505029 0.012961403
2000 10 1.177296593 0.015340024
2001 10 1.2922 0.014787016
2002 10 1.4391 0.014294892
2003 10 1.6809 0.015911837
2004 10 2.0705 0.015915512
2005 10 2.456 0.017551839
2006 10 2.8814 0.016437086
2007 10 3.3928 0.015220102
1997 11 1.046026024 0.009264216
1998 11 1.122234723 0.013697195
1999 11 1.203656589 0.013589676
2000 11 1.346093294 0.012012978
2001 11 1.4655 0.012046607
2002 11 1.6838 0.0127796
2003 11 2.0147 0.015114081
2004 11 2.3942 0.016716102
2005 11 2.770268465 0.016966109
2006 11 3.1874 0.016646586
2007 11 3.7411 0.015309062
1997 12 0.436127462 0.005423323
1998 12 0.454852637 0.006129738
1999 12 0.470722241 0.005840917
2000 12 0.486740767 0.005857417
2001 12 0.522077118 0.005511109
2002 12 0.5817 0.005507857
2003 12 0.6455 0.00632376
2004 12 0.7768 0.006794614
2005 12 0.867514475 0.008415033
2006 12 1.0055 0.008494272
2007 12 1.2045 0.008446094
1997 13 0.914848222 0.003572334
1998 13 1.028210382 0.004696423
1999 13 1.079687733 0.00511351
2000 13 1.160127257 0.006175108
2001 13 1.2362 0.005410494
2002 13 1.3497 0.005227813
2003 13 1.4979 0.008402322
2004 13 1.7218 0.008829393
2005 13 1.864584161 0.01241867
2006 13 2.1471 0.012535132
2007 13 2.5908 0.011920659
1997 14 0.413355207 0.005217518
1998 14 0.443120392 0.005817633
1999 14 0.466134513 0.005595486
2000 14 0.48512583 0.00695913
2001 14 0.5221 0.006187339
2002 14 0.5829 0.00587648
2003 14 0.6678 0.009208388
2004 14 0.8189 0.010947712
2005 14 0.944 0.012874043
2006 14 1.0798 0.013136667
2007 14 1.2633 0.012669719
1997 15 0.757633084 0.017037439
1998 15 0.815639144 0.019914653
1999 15 0.867346997 0.016340729
2000 15 0.955523789 0.016091001
2001 15 1.0465 0.015581418
2002 15 1.1645 0.015347545
2003 15 1.3661 0.016877699
2004 15 1.6925 0.016819172
2005 15 2.009645474 0.01854455
2006 15 2.3794 0.018122247
2007 15 2.7807 0.01689622
1997 16 0.441301606 0.00736367
1998 16 0.468741052 0.008243317
1999 16 0.489370121 0.00722692
2000 16 0.544387815 0.008074589
2001 16 0.592355196 0.007953312
2002 16 0.6436 0.008398564
2003 16 0.757017506 0.009327547
2004 16 0.947 0.011454153
2005 16 1.134649798 0.015682303
2006 16 1.3313 0.015587734
2007 16 1.6012 0.015066276
1997 17 0.587402825 0.006586668
1998 17 0.635003836 0.008322397
1999 17 0.651397012 0.008484136
2000 17 0.718827639 0.008430956
2001 17 0.781307 0.008106661
2002 17 0.8319 0.007895775
2003 17 0.90107 0.009044671
2004 17 1.05 0.010106383
2005 17 1.1431 0.010963222
2006 17 1.3296 0.011487792
2007 17 1.6206 0.010588466
1997 18 0.463055885 0.007242954
1998 18 0.497090268 0.009516826
1999 18 0.51047261 0.009283114
2000 18 0.563901494 0.009728168
2001 18 0.6054 0.008897044
2002 18 0.6565 0.00868754
2003 18 0.7554 0.010076679
2004 18 0.9117 0.010630039
2005 18 1.0426 0.011934872
2006 18 1.195 0.012078209
2007 18 1.4492 0.011635407
1997 19 1.038356826 0.006755595
1998 19 1.140140153 0.009003024
1999 19 1.172829429 0.009207648
2000 19 1.288539579 0.010200856
2001 19 1.372992858 0.012006938
2002 19 1.503 0.01211336
2003 19 1.721306989 0.013254046
2004 19 1.9707 0.013583815
2005 19 2.443501564 0.013856863
2006 19 2.8332 0.013402837
2007 19 3.3151 0.012447478
1997 20 0.434562921 0.010752903
1998 20 0.407330494 0.013764385
1999 20 0.414795073 0.011638001
2000 20 0.431881188 0.017832145
2001 20 0.4668 0.013839265
2002 20 0.5099 0.013400954
2003 20 0.5969 0.017098394
2004 20 0.7196 0.01834731
2005 20 0.878772899 0.020922747
2006 20 1.0296 0.020004238
2007 20 1.2555 0.019426322
1997 21 0.550817143 0.002273351
1998 21 0.589271833 0.002674236
1999 21 0.638298161 0.002906562
2000 21 0.689394745 0.002563914
2001 21 0.7135 0.002422487
2002 21 0.7803 0.002744334
2003 21 0.8316 0.00276884
2004 21 0.945 0.002689487
2005 21 1.0871 0.002657005
2006 21 1.2654 0.002751196
2007 21 1.4555 0.002951917
1997 22 0.443858918 0.01303833
1998 22 0.467244732 0.011888366
1999 22 0.482617474 0.024674959
2000 22 0.515731475 0.02149644
2001 22 0.5654 0.018386116
2002 22 0.6347 0.017760541
2003 22 0.7209 0.019589105
2004 22 0.9608 0.02053171
2005 22 1.0982 0.024410293
2006 22 1.2457 0.025356125
2007 22 1.466 0.024256397
1997 23 0.393875874 0.007606145
1998 23 0.423952752 0.0084499
1999 23 0.445190371 0.006153883
2000 23 0.478376579 0.011934974
2001 23 0.525 0.010888565
2002 23 0.5766 0.010724882
2003 23 0.6418 0.01207464
2004 23 0.8113 0.012595989
2005 23 0.906 0.013894301
2006 23 1.0546 0.01372261
2007 23 1.2893 0.012589131
1997 24 0.219941492 0.016895452
1998 24 0.232595344 0.023279005
1999 24 0.247530423 0.018296765
2000 24 0.266155713 0.018226667
2001 24 0.289529025 0.015040984
2002 24 0.3153 0.015040318
2003 24 0.3603 0.01473654
2004 24 0.4215 0.015368852
2005 24 0.505196 0.01766756
2006 24 0.5787 0.027681661
2007 24 0.6915 0.024470653
1997 25 0.401677771 0.006605447
1998 25 0.432688303 0.00739971
1999 25 0.445224443 0.006598187
2000 25 0.463665038 0.007552542
2001 25 0.4866 0.006867833
2002 25 0.5179 0.006764713
2003 25 0.5662 0.008700133
2004 25 0.6733 0.009060023
2005 25 0.7835 0.009640449
2006 25 0.897 0.01017176
2007 25 1.054 0.009866885
1997 26 0.371462307 0.015350476
1998 26 0.389195944 0.015607675
1999 26 0.410148883 0.015827584
2000 26 0.454921939 0.015360277
2001 26 0.5024 0.014819377
2002 26 0.5523 0.015081083
2003 26 0.648 0.017645643
2004 26 0.7757 0.019055331
2005 26 0.9899 0.021505376
2006 26 1.2138 0.022650602
2007 26 1.4607 0.022560801
1997 27 0.313276022 0.014349318
1998 27 0.345166012 0.013183089
1999 27 0.36677686 0.010117263
2000 27 0.383825137 0.012173224
2001 27 0.416335736 0.012247107
2002 27 0.4493 0.014415889
2003 27 0.502163236 0.016943811
2004 27 0.597 0.01672394
2005 27 0.747652929 0.019930609
2006 27 0.8757 0.017766692
2007 27 1.0346 0.016651318
1997 28 0.407711619 0.00509879
1998 28 0.43866956 0.003887674
1999 28 0.46624291 0.003723922
2000 28 0.508713693 0.003895174
2001 28 0.573456555 0.004528872
2002 28 0.6426 0.004180529
2003 28 0.7277 0.009464593
2004 28 0.8606 0.01187384
2005 28 1.004474034 0.021178637
2006 28 1.1762 0.022080292
2007 28 1.4257 0.022691806
1997 29 0.398021397 0.035038302
1998 29 0.425513243 0.03457342
1999 29 0.447261682 0.032364825
2000 29 0.48391035 0.030988434
2001 29 0.534 0.029978863
2002 29 0.5804 0.032730769
2003 29 0.6691 0.044523867
2004 29 0.788 0.044217687
2005 29 1.0239 0.050671141
2006 29 1.1847 0.05794702
2007 29 1.4649 0.055741257
1997 30 0.611323119 0.009333993
1998 30 0.648331053 0.010956039
1999 30 0.64697317 0.011156088
2000 30 0.746980564 0.009750078
2001 30 0.7913 0.010071482
2002 30 0.8382 0.010132861
2003 30 0.97 0.011545748
2004 30 1.1199 0.016046867
2005 30 1.3108 0.017313433
2006 30 1.5 0.020926829
2007 30 1.6999 0.022555503
;
proc sort data=so2;
by state year;
run;
威布尔方程的形式是：
model so2=e+log(a)-log(b)+(a-1)*log((income-c)/b)-((income-c)/b)**a+d/(((income-c)/b)**a) / fixone;
id state year;
求教如何排列这几个语句的形式。。。
定重谢！！！！！！！！

估计方法可以使用极大似然 这个没有问题。。。 只要是利用面板数据估计出了那个方程就行了。。。
谢谢！！！

自己顶 希望有牛人快快出现！

这个应该是很多人都做过的东西啊 没那么难吧  好歹有个人回答啊。。。

我也面临这个问题啊

请教什么是威布尔方程，它是干什么用的？

请教什么是威布尔方程，它是干什么用的？