1 AT_BANNER([LINEAR REGRESSION])
3 AT_SETUP([LINEAR REGRESSION - basic])
4 AT_DATA([regression.sps], [dnl
6 data list notable list / v0 to v2.
9 0.65377128 7.735648 -23.97588
10 -0.13087553 6.142625 -19.63854
11 0.34880368 7.651430 -25.26557
12 0.69249021 6.125125 -16.57090
13 -0.07368178 8.245789 -25.80001
14 -0.34404919 6.031540 -17.56743
15 0.75981559 9.832291 -28.35977
16 -0.46958313 5.343832 -16.79548
17 -0.06108490 8.838262 -29.25689
18 0.56154863 6.200189 -18.58219
20 regression /variables=v0 v1 v2 /statistics defaults /dependent=v2 /method=enter /save=pred resid.
24 AT_CHECK([pspp -O format=csv regression.sps], [0], [dnl
25 regression.sps:16: warning: REGRESSION: REGRESSION with SAVE ignores FILTER. All cases will be processed.
27 Table: Model Summary (v2)
28 ,R,R Square,Adjusted R Square,Std. Error of the Estimate
32 ,,Sum of Squares,df,Mean Square,F,Sig.
33 ,Regression,202.753,2,101.376,56.754,.000
34 ,Residual,12.504,7,1.786,,
37 Table: Coefficients (v2)
38 ,,Unstandardized Coefficients,,Standardized Coefficients,,
39 ,,B,Std. Error,Beta,t,Sig.
40 ,(Constant),2.191,2.357,.000,.930,.380
41 ,v0,1.813,1.053,.171,1.722,.129
42 ,v1,-3.427,.332,-1.026,-10.334,.000
46 .654,7.736,-23.976,-.84,-23.13
47 -.131,6.143,-19.639,-.54,-19.10
48 .349,7.651,-25.266,-1.87,-23.40
49 .692,6.125,-16.571,.97,-17.54
50 -.074,8.246,-25.800,.40,-26.20
51 -.344,6.032,-17.567,1.53,-19.10
52 .760,9.832,-28.360,1.77,-30.13
53 -.470,5.344,-16.795,.18,-16.97
54 -.061,8.838,-29.257,-1.05,-28.21
55 .562,6.200,-18.582,-.54,-18.04
60 AT_SETUP([LINEAR REGRESSION - one save])
61 AT_DATA([regression.sps], [dnl
63 data list notable list / v0 to v2.
65 0.65377128 7.735648 -23.97588
66 -0.13087553 6.142625 -19.63854
67 0.34880368 7.651430 -25.26557
68 0.69249021 6.125125 -16.57090
69 -0.07368178 8.245789 -25.80001
70 -0.34404919 6.031540 -17.56743
71 0.75981559 9.832291 -28.35977
72 -0.46958313 5.343832 -16.79548
73 -0.06108490 8.838262 -29.25689
74 0.56154863 6.200189 -18.58219
76 regression /variables=v0 v1 v2 /statistics defaults /dependent=v2 /method=enter /save=resid.
77 regression /variables=v0 v1 v2 /statistics defaults /dependent=v2 /method=enter /save=pred.
81 AT_CHECK([pspp -O format=csv regression.sps], [0], [dnl
82 Table: Model Summary (v2)
83 ,R,R Square,Adjusted R Square,Std. Error of the Estimate
87 ,,Sum of Squares,df,Mean Square,F,Sig.
88 ,Regression,202.753,2,101.376,56.754,.000
89 ,Residual,12.504,7,1.786,,
92 Table: Coefficients (v2)
93 ,,Unstandardized Coefficients,,Standardized Coefficients,,
94 ,,B,Std. Error,Beta,t,Sig.
95 ,(Constant),2.191,2.357,.000,.930,.380
96 ,v0,1.813,1.053,.171,1.722,.129
97 ,v1,-3.427,.332,-1.026,-10.334,.000
99 Table: Model Summary (v2)
100 ,R,R Square,Adjusted R Square,Std. Error of the Estimate
101 ,.971,.942,.925,1.337
104 ,,Sum of Squares,df,Mean Square,F,Sig.
105 ,Regression,202.753,2,101.376,56.754,.000
106 ,Residual,12.504,7,1.786,,
109 Table: Coefficients (v2)
110 ,,Unstandardized Coefficients,,Standardized Coefficients,,
111 ,,B,Std. Error,Beta,t,Sig.
112 ,(Constant),2.191,2.357,.000,.930,.380
113 ,v0,1.813,1.053,.171,1.722,.129
114 ,v1,-3.427,.332,-1.026,-10.334,.000
118 .654,7.736,-23.976,-.84,-23.13
119 -.131,6.143,-19.639,-.54,-19.10
120 .349,7.651,-25.266,-1.87,-23.40
121 .692,6.125,-16.571,.97,-17.54
122 -.074,8.246,-25.800,.40,-26.20
123 -.344,6.032,-17.567,1.53,-19.10
124 .760,9.832,-28.360,1.77,-30.13
125 -.470,5.344,-16.795,.18,-16.97
126 -.061,8.838,-29.257,-1.05,-28.21
127 .562,6.200,-18.582,-.54,-18.04
132 # Test to ensure that the /SAVE subcommand works properly when SPLIT is active
133 AT_SETUP([LINEAR REGRESSION - SAVE vs SPLITS])
135 # Generate some test data based on a linear model
136 AT_DATA([gen-data.sps], [dnl
140 compute x0 = rv.normal (0,1).
141 compute x1 = rv.normal (0,2).
142 compute err = rv.normal (0,0.1).
143 compute y = 4 - 2 * x0 + 3 * x1 + err.
144 compute g = (#c > 10).
150 print outfile='regdata.txt' /g x0 x1 y err *.
154 AT_CHECK([pspp -O format=csv gen-data.sps], [0], [ignore])
156 # Use our test data to create a predictor and a residual variable
158 AT_DATA([regression0.sps], [dnl
159 data list notable file='regdata.txt' list /g x0 x1 y err *.
170 print outfile='outdata-g0.txt' /g x0 x1 y err res1 pred1 *.
175 AT_CHECK([pspp -O format=csv regression0.sps], [0], [ignore])
177 # Use our test data to create a predictor and a residual variable
179 AT_DATA([regression1.sps], [dnl
180 data list notable file='regdata.txt' list /g x0 x1 y err *.
191 print outfile='outdata-g1.txt' /g x0 x1 y err res1 pred1 *.
196 AT_CHECK([pspp -O format=csv regression1.sps], [0], [ignore])
198 # Use our test data to create a predictor and a residual variable
199 # The data is split on G
200 AT_DATA([regression-split.sps], [dnl
201 data list notable file='regdata.txt' list /g x0 x1 y err *.
212 print outfile='outdata-split.txt' /g x0 x1 y err res1 pred1 *.
216 AT_CHECK([pspp -O format=csv regression-split.sps], [0], [ignore])
218 # The concatenation of G==0 and G==1 should be identical to the SPLIT data
219 AT_CHECK([cat outdata-g0.txt outdata-g1.txt | diff outdata-split.txt - ], [0], [])
224 # Test that the procedure behaves sensibly when presented with
225 # multiple dependent variables
226 AT_SETUP([LINEAR REGRESSION multiple dependent variables])
227 AT_DATA([regression.sps], [dnl
231 compute x0 = rv.normal (0, 1).
232 compute x1 = rv.normal (0, 2).
233 compute err = rv.normal (0, 0.8).
234 compute y = 2 - 1.5 * x0 + 8.4 * x1 + err.
244 /statistics = default.
247 AT_CHECK([pspp -O format=csv regression.sps > output], [0], [ignore])
249 AT_CHECK([head -16 output > first], [0], [])
250 AT_CHECK([tail -16 output > second], [0], [])
252 AT_CHECK([sed -e 's/ycopy/y/g' second | diff first -], [0], [])
257 # Tests the QR decomposition used by the REGRESSION command.
258 AT_SETUP([LINEAR REGRESSION test of QR decomposition])
259 AT_DATA([regression.sps], [dnl
260 data list list / v0 to v1.
262 -12.84099361 0.873270778
263 16.64932538 0.371315664
264 -1.88061907 0.505503722
265 -6.20952354 0.734698282
266 0.33272576 0.891224610
267 -5.54912717 0.052318165
268 6.11832417 0.448853404
269 11.78124974 0.470447593
270 0.75960353 0.565082303
271 6.06432768 0.149316743
272 -2.64919436 0.752532411
273 -10.32250712 0.798263603
274 2.06355038 0.469129797
275 -9.71851742 0.927162270
276 4.65582553 0.250629262
277 9.54574474 0.847032310
278 7.35544368 0.197028541
279 -2.09609740 0.400584261
280 10.30101161 0.671546480
281 -5.24501039 0.929962876
282 1.73412473 0.758161354
283 -3.12732732 0.569785505
284 12.66261501 0.630640223
285 -2.90956805 0.576067804
286 4.89649177 0.624483995
287 13.64613114 0.591089881
288 14.03198397 0.544587572
289 2.23566810 0.967898139
290 5.37367760 0.916246929
291 9.01346888 0.451702743
292 0.75378683 0.235544137
293 -3.47470624 0.742668194
294 -1.02063266 0.860311687
295 -2.67132813 0.082460702
296 23.67661680 0.932553932
297 7.95061359 0.430161125
298 2.05300558 0.066331375
299 -2.01332644 0.163705417
300 20.00663784 0.587292630
301 3.06099417 0.161411889
302 -3.46115358 0.216684625
303 -6.85287183 0.548714855
304 -4.27923809 0.630997663
305 -0.94863395 0.880612945
306 4.47481747 0.359885215
307 -12.80962955 0.886070341
308 9.35753086 0.187176558
309 2.81002235 0.063035095
310 0.01532424 0.964327101
311 0.29867732 0.866408063
312 -2.89035649 0.812135868
313 4.17352811 0.608884061
314 18.15502183 0.920568258
315 -2.92662792 0.550792959
316 -6.08090449 0.965036595
317 -1.09135397 0.862548019
318 7.02816784 0.042277017
319 -21.20245068 0.430673493
320 -8.83397584 0.724976162
321 -0.89055843 0.017934904
322 7.03871587 0.308829557
323 3.84286316 0.685105924
324 4.50280692 0.447635420
325 11.39207346 0.875177896
326 10.86673874 0.518530912
327 7.09853081 0.588367569
328 -12.82864915 0.184667098
329 13.74888760 0.610891139
330 0.37379146 0.557720134
331 -9.79020267 0.942839981
332 0.71574466 0.564570338
333 -17.56040637 0.182061777
334 2.52620466 0.306875011
335 5.37718673 0.366807049
336 -1.83964300 0.465772898
337 6.04848363 0.644501799
338 4.57402403 0.121419591
339 8.55606848 0.373011464
340 -8.46827907 0.491176571
341 -1.77989798 0.734722847
342 -0.68661121 0.540984182
343 1.55798880 0.822587656
344 5.22810831 0.333747878
345 9.50280477 0.068100934
346 -3.74521465 0.248537644
347 1.36045068 0.851827791
348 4.41604088 0.197207162
349 -3.72568327 0.726916693
350 -5.36123334 0.906513529
351 3.61594583 0.414340595
352 -10.01952852 0.140372658
353 25.48681482 0.354309660
354 -3.34529093 0.090075388
355 -18.00437582 0.461438059
356 -5.29782460 0.004362856
357 2.79608522 0.861294398
358 -1.64076209 0.345775481
359 6.82802334 0.137933862
360 -0.45416818 0.404379208
361 -1.66868582 0.797685201
362 -10.02820292 0.075876582
363 5.68232031 0.404815042
364 8.25113850 0.769173748
365 -2.83544237 0.076583474
366 0.87659945 0.092751009
367 6.60270870 0.530444351
368 -12.63924989 0.362099960
369 -6.24451253 0.641993458
370 3.53339015 0.461991892
371 -0.74012232 0.437409755
372 15.37311996 0.974913038
373 -8.09464797 0.543308711
374 -9.61320222 0.221564578
375 0.21843662 0.856512540
376 -1.56958954 0.610709221
377 6.44977372 0.200382138
378 -13.29136274 0.093222309
379 6.46257214 0.024135196
380 -3.82727990 0.601335801
381 0.43081953 0.268230667
382 19.06654416 0.219972815
383 17.02906651 0.996849502
384 -10.18073139 0.012543080
385 12.72088788 0.910600764
386 10.45328185 0.331285901
387 7.14370922 0.896312020
388 -2.81754334 0.048741266
389 6.40217095 0.075796756
390 -3.18030478 0.666325307
391 8.64585957 0.120549153
392 1.37952764 0.899991932
393 -11.81143886 0.601949630
394 0.03899706 0.363808260
395 -10.63828243 0.031092967
396 -6.66940972 0.246204205
397 -5.07374962 0.951272057
398 4.82281566 0.063928187
399 -21.93693564 0.050972680
400 -4.54569883 0.225839693
401 -0.92422779 0.437796785
402 -1.11683029 0.740215139
403 16.77765554 0.851072372
404 9.73614597 0.388180586
405 14.05345168 0.063760129
406 1.20512012 0.665964184
407 8.00307080 0.102447114
408 8.01252623 0.580929209
409 -13.54924183 0.438420739
410 9.87164361 0.970859344
411 17.63437095 0.250501797
412 -3.42503574 0.873290220
413 -2.45873197 0.847756049
414 17.29212092 0.411683187
415 1.15496098 0.530658504
416 -2.14438907 0.592255367
417 -1.79942021 0.517773009
418 -1.30677990 0.830860762
419 1.70233874 0.291826660
420 -3.05532536 0.801767829
421 -4.06732625 0.092294501
422 6.34665476 0.270426235
423 9.46946411 0.196915311
424 14.50919907 0.480357167
425 8.93767237 0.778228613
426 1.90298854 0.903146151
427 18.50500507 0.598561307
428 4.45123027 0.555898218
429 11.37344114 0.616557707
430 -12.14693218 0.409187285
431 18.27198688 0.141619222
432 -5.75939569 0.056989619
433 -4.05515382 0.369281201
434 16.69882098 0.946885257
435 6.39050536 0.679704228
436 4.04213339 0.662792380
437 6.89608366 0.419877433
438 1.56496633 0.358227958
439 5.16679947 0.095144366
440 -3.06280456 0.883265975
441 2.76279175 0.866571973
442 1.84969249 0.264869828
443 21.79840498 0.702650979
444 1.42450528 0.719308635
445 0.96797046 0.111937435
446 18.26840323 0.075621738
447 13.38288377 0.573399086
448 2.41101500 0.766238677
449 3.83866337 0.499888953
450 -1.56577367 0.695244089
451 -0.90342790 0.671654151
452 10.83775583 0.026041124
453 -9.89767935 0.745297991
454 11.74840150 0.309144074
455 1.73069359 0.814063985
456 -5.27966183 0.591005828
457 3.33030043 0.559401806
458 1.31427975 0.520950237
459 -10.04588558 0.507008362
460 10.41228345 0.425867272
461 1.71961097 0.595783108
462 -17.54904427 0.328788939
463 -2.23545419 0.223377350
464 -8.68774333 0.980964240
465 -3.48048220 0.008877675
466 -3.69635326 0.090236718
467 9.76114237 0.769375983
468 -10.25662038 0.508137553
469 0.11155446 0.468504431
470 -8.06824580 0.414098962
471 3.10031660 0.327130207
472 -3.33393146 0.756896774
473 -3.96276749 0.530956360
474 14.53610268 0.846474699
475 1.70505918 0.754662464
476 -1.93495001 0.656650411
477 5.01974522 0.745337633
478 13.41249973 0.489362476
479 11.49288744 0.335924476
480 12.59019763 0.155560469
481 -10.17947298 0.677318449
482 0.05556115 0.655090105
483 3.82092860 0.051838719
484 8.23041456 0.918272190
485 -0.50314649 0.772015826
486 20.05162157 0.880265258
487 8.98816884 0.666646668
488 -6.28312120 0.138534416
489 3.68589909 0.274559458
490 0.59699510 0.253180863
491 -2.74783135 0.983525221
492 0.32515065 0.839969577
493 -3.60606166 0.330646732
494 -0.82037740 0.129591173
495 6.12444860 0.098536516
496 10.95671074 0.033546728
497 -2.84911174 0.720288722
498 6.04597572 0.577061422
499 -0.60147150 0.674096868
500 -5.30458364 0.291468008
501 2.68044943 0.379853840
502 0.85986585 0.984214339
503 -12.77906359 0.882390290
504 7.21420144 0.550884826
505 2.31817022 0.231021556
506 11.60161950 0.888496654
507 -0.19346228 0.242609713
508 5.07478120 0.759161318
509 14.54155003 0.040387654
510 3.81039636 0.874572741
511 2.23233049 0.448317248
512 0.19481869 0.201906051
513 2.81530451 0.132131690
514 12.39893259 0.674693704
515 0.47054642 0.632959494
516 2.16152913 0.734480632
517 0.33398836 0.315024718
518 7.35509037 0.304570986
519 -2.92336559 0.539062343
520 5.79622573 0.392393310
521 -2.37607425 0.403380474
522 0.04498550 0.756875541
523 -1.63674414 0.613789514
524 11.80310547 0.832651469
525 6.30630243 0.850689403
526 1.48394652 0.096243229
527 4.03361865 0.799660045
528 3.54707273 0.408520520
529 2.00327040 0.702944912
530 17.30761707 0.380542812
531 5.72738968 0.105447516
532 -13.64604891 0.328506659
533 8.35976334 0.702173924
534 -7.41197443 0.134396488
535 -15.95683040 0.618526462
536 8.76889573 0.950243069
537 -1.13482624 0.113477080
538 -0.60311407 0.090444247
539 4.95508365 0.612511543
540 5.36934491 0.979213258
541 -0.03554882 0.807185690
542 -11.58131144 0.183341373
543 4.46809041 0.796330582
544 12.49741067 0.346860912
545 8.63824488 0.073684997
546 0.49990913 0.732519306
547 12.82688360 0.109400213
548 13.20375065 0.850369092
549 -8.41110869 0.177717087
550 16.31959963 0.727704840
551 17.59203613 0.235311681
552 0.32148420 0.842195936
553 5.43148331 0.670904647
554 7.14649727 0.028190029
555 0.25410683 0.421535783
556 -12.41047826 0.086404379
557 -10.64180909 0.229659236
558 -6.40185653 0.876365242
559 15.63063324 0.667672536
560 1.94280423 0.799266628
561 -5.76507450 0.367344192
562 8.60895533 0.154109357
563 9.38306751 0.788742770
564 3.43573528 0.284535277
565 4.81848966 0.872283177
566 11.65839314 0.234109111
567 -5.57884822 0.030363060
568 -3.94238060 0.325320686
569 9.38133340 0.201141788
570 -7.65003459 0.647734396
571 11.23091019 0.084927159
572 -6.07705432 0.037273791
573 7.46380750 0.506897136
574 7.42034855 0.869351148
575 -4.43031973 0.231191152
576 -1.07351537 0.480234836
577 -1.40653281 0.690620421
578 -3.82710168 0.990191328
579 5.04583490 0.543427375
580 -11.54265099 0.270542185
581 0.49059479 0.991447248
582 -1.40871469 0.555998766
583 3.64241437 0.743840673
584 -18.30031589 0.357478210
585 4.27487959 0.770619738
586 1.28805821 0.654787106
587 -3.19542768 0.218110139
588 12.53375654 0.011857644
589 11.78889419 0.054127726
590 -5.38392310 0.839309080
591 16.38024181 0.228801038
592 -0.59622631 0.134381782
593 -0.74107258 0.258146632
594 -12.31429450 0.020524447
595 -0.79785028 0.968028764
596 6.39899711 0.038162566
597 7.42024044 0.716163692
598 -3.62470664 0.018201813
599 -2.55049724 0.162446610
600 -10.79888854 0.683070478
601 10.18490144 0.546461234
602 -2.76979044 0.198830067
603 4.85164813 0.094100357
604 0.96477200 0.381801756
605 8.13344336 0.639730450
606 9.04684412 0.786084368
607 10.41746272 0.828304181
608 0.94334368 0.798419831
609 10.13116556 0.191715972
610 -4.12728628 0.575178239
611 -9.59222379 0.876405375
612 1.64680258 0.391003085
613 -4.58897613 0.039176486
614 0.38394379 0.511577564
615 -4.80428215 0.222785463
616 0.35363661 0.681658725
617 -9.63685708 0.183035382
618 3.54363414 0.766127414
619 6.89610808 0.967514568
620 -2.03781105 0.464416752
621 8.67956196 0.421424078
622 -1.09959038 0.061231448
623 7.12587456 0.028601318
624 -6.93064672 0.402561175
625 8.57989199 0.925089270
626 -9.55071810 0.454993099
627 -8.11914736 0.509644286
628 -5.41909698 0.077813151
629 -17.03336572 0.875713545
630 -1.27438609 0.602163625
631 3.09834374 0.105599007
632 -1.59865741 0.439939102
633 11.82272089 0.754984309
634 4.30969696 0.483834579
635 -10.76886192 0.222486992
636 7.05419803 0.903020271
637 7.36096847 0.440357053
638 -2.05864869 0.581170147
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1691 8.43735652 0.275383759
1692 -15.56161079 0.413160084
1693 5.28942694 0.069125495
1694 5.96040877 0.438716686
1695 -2.59318107 0.571116303
1696 6.95988992 0.650760909
1697 14.00074797 0.623645969
1698 1.66101456 0.558763985
1699 -2.57968349 0.648185379
1700 -5.47584253 0.716901151
1701 6.37222581 0.060563130
1702 2.83664864 0.842419730
1703 1.48926558 0.620280308
1704 0.33471689 0.170312461
1705 5.21648412 0.317639631
1706 0.51733642 0.843867329
1707 9.86005834 0.306036746
1708 -5.81145791 0.975655452
1709 -5.43219061 0.303385368
1710 5.87157118 0.677369776
1711 2.08889926 0.310200439
1712 -2.53433085 0.194730908
1713 7.01359575 0.674259533
1714 -2.00936260 0.682056466
1715 -2.98240739 0.787899917
1716 -7.43289210 0.357483044
1717 -12.58905988 0.981387385
1718 5.78095517 0.533526274
1719 -1.23065889 0.687266774
1720 -6.82309960 0.293249774
1721 8.47000829 0.842056399
1722 -5.81624772 0.303700280
1723 -14.83571031 0.311387926
1724 4.66808472 0.091222946
1725 -2.90144463 0.438301785
1726 10.62458662 0.828335698
1727 7.88002491 0.990156110
1728 10.27680283 0.251087079
1729 -9.42498970 0.292462244
1730 6.73027640 0.213065205
1731 1.28169895 0.353152789
1732 -14.29203733 0.264563048
1733 20.35772711 0.265208837
1734 3.55095071 0.242905653
1735 -17.97067670 0.373951756
1736 10.53141139 0.247520698
1737 0.05293205 0.579940423
1738 12.79674707 0.288031751
1739 -5.44235185 0.075899079
1740 14.29464811 0.960707538
1741 -1.36753291 0.124265178
1742 -4.25946974 0.521720352
1743 -12.46519252 0.385503339
1744 -6.65343143 0.540942219
1745 5.55949184 0.143194404
1746 -1.20480594 0.515905644
1747 -4.13839908 0.164461445
1748 -2.21345425 0.812969725
1749 3.94223380 0.229238952
1750 -10.78661097 0.395049514
1751 3.06997341 0.791234255
1752 24.82205477 0.110859039
1753 6.28791249 0.867125744
1754 -2.80296119 0.703583849
1755 13.24274039 0.425951975
1756 -0.19577471 0.361568727
1757 -2.34894781 0.954814545
1758 19.76339577 0.635462177
1759 -1.87591480 0.149121567
1760 -7.70962391 0.711708342
1761 -2.46291902 0.390902746
1763 regression /variables=v0 v1 /statistics defaults /dependent=v0 /method=enter.
1766 AT_CHECK([pspp -O format=csv regression.sps], [0], [dnl
1767 Table: Reading free-form data from INLINE.
1772 Table: Model Summary (v0)
1773 ,R,R Square,Adjusted R Square,Std. Error of the Estimate
1777 ,,Sum of Squares,df,Mean Square,F,Sig.
1778 ,Regression,235.23,1,235.23,3.58,.059
1779 ,Residual,98438.40,1498,65.71,,
1780 ,Total,98673.63,1499,,,
1782 Table: Coefficients (v0)
1783 ,,Unstandardized Coefficients,,Standardized Coefficients,,
1784 ,,B,Std. Error,Beta,t,Sig.
1785 ,(Constant),1.24,.42,.00,2.95,.003
1786 ,v1,1.37,.72,.05,1.89,.059
1791 AT_SETUP([LINEAR REGRESSION no crash on all missing])
1792 AT_DATA([regcrash.sps], [dnl
1793 data list list /x * y.
1808 regression /variables=x y /dependent=y.
1811 AT_CHECK([pspp -o pspp.csv regcrash.sps], [1], [ignore], [ignore])
1817 AT_SETUP([LINEAR REGRESSION missing dependent variable])
1819 dnl Test for a bug where missing values in the dependent variable were not being
1820 dnl ignored like they should have been.
1821 AT_DATA([reg-mdv-ref.sps], [dnl
1822 data list notable list / v0 to v2.
1824 0.65377128 7.735648 -23.97588
1825 -0.13087553 6.142625 -19.63854
1826 0.34880368 7.651430 -25.26557
1827 0.69249021 6.125125 -16.57090
1828 -0.07368178 8.245789 -25.80001
1829 -0.34404919 6.031540 -17.56743
1830 0.75981559 9.832291 -28.35977
1831 -0.46958313 5.343832 -16.79548
1832 -0.06108490 8.838262 -29.25689
1833 0.56154863 6.200189 -18.58219
1835 regression /variables=v0 v1
1836 /statistics defaults
1841 AT_CHECK([pspp -o pspp-ref.csv reg-mdv-ref.sps])
1843 AT_DATA([reg-mdv.sps], [dnl
1844 data list notable list / v0 to v2.
1846 0.65377128 7.735648 -23.97588
1847 -0.13087553 6.142625 -19.63854
1848 0.34880368 7.651430 -25.26557
1849 0.69249021 6.125125 -16.57090
1850 -0.07368178 8.245789 -25.80001
1851 -0.34404919 6.031540 -17.56743
1852 0.75981559 9.832291 -28.35977
1853 -0.46958313 5.343832 -16.79548
1854 -0.06108490 8.838262 -29.25689
1855 0.56154863 6.200189 -18.58219
1859 missing values v2 (9).
1861 regression /variables=v0 v1
1862 /statistics defaults
1867 AT_CHECK([pspp -o pspp.csv reg-mdv.sps])
1869 AT_CHECK([diff pspp.csv pspp-ref.csv])
1874 AT_SETUP([LINEAR REGRESSION with invalid syntax (and empty dataset)])
1876 AT_DATA([ss.sps], [dnl
1877 data list notable list / v0 to v2.
1881 regression /variables=v0 v1
1882 /statistics r coeff anova
1887 AT_CHECK([pspp ss.sps], [1], [ignore])
1892 dnl The following example comes from
1893 dnl http://www.ats.ucla.edu/stat/spss/output/reg_spss%28long%29.htm
1894 AT_SETUP([LINEAR REGRESSION coefficient confidence interval])
1896 AT_DATA([conf.sps], [dnl
1899 data list notable list /math female socst read science *
1901 41.00 .00 57.00 57.00 47.00
1902 53.00 1.00 61.00 68.00 63.00
1903 54.00 .00 31.00 44.00 58.00
1904 47.00 .00 56.00 63.00 53.00
1905 57.00 .00 61.00 47.00 53.00
1906 51.00 .00 61.00 44.00 63.00
1907 42.00 .00 61.00 50.00 53.00
1908 45.00 .00 36.00 34.00 39.00
1909 54.00 .00 51.00 63.00 58.00
1910 52.00 .00 51.00 57.00 50.00
1911 51.00 .00 61.00 60.00 53.00
1912 51.00 .00 61.00 57.00 63.00
1913 71.00 .00 71.00 73.00 61.00
1914 57.00 .00 46.00 54.00 55.00
1915 50.00 .00 56.00 45.00 31.00
1916 43.00 .00 56.00 42.00 50.00
1917 51.00 .00 56.00 47.00 50.00
1918 60.00 .00 56.00 57.00 58.00
1919 62.00 .00 61.00 68.00 55.00
1920 57.00 .00 46.00 55.00 53.00
1921 35.00 .00 41.00 63.00 66.00
1922 75.00 .00 66.00 63.00 72.00
1923 45.00 .00 56.00 50.00 55.00
1924 57.00 .00 61.00 60.00 61.00
1925 45.00 .00 46.00 37.00 39.00
1926 46.00 .00 31.00 34.00 39.00
1927 66.00 .00 66.00 65.00 61.00
1928 57.00 .00 46.00 47.00 58.00
1929 49.00 .00 46.00 44.00 39.00
1930 49.00 .00 41.00 52.00 55.00
1931 57.00 .00 51.00 42.00 47.00
1932 64.00 .00 61.00 76.00 64.00
1933 63.00 .00 71.00 65.00 66.00
1934 57.00 .00 31.00 42.00 72.00
1935 50.00 .00 61.00 52.00 61.00
1936 58.00 .00 66.00 60.00 61.00
1937 75.00 .00 66.00 68.00 66.00
1938 68.00 .00 66.00 65.00 66.00
1939 44.00 .00 36.00 47.00 36.00
1940 40.00 .00 51.00 39.00 39.00
1941 41.00 .00 51.00 47.00 42.00
1942 62.00 .00 51.00 55.00 58.00
1943 57.00 .00 51.00 52.00 55.00
1944 43.00 .00 41.00 42.00 50.00
1945 48.00 .00 66.00 65.00 63.00
1946 63.00 .00 46.00 55.00 69.00
1947 39.00 .00 47.00 50.00 49.00
1948 70.00 .00 51.00 65.00 63.00
1949 63.00 .00 46.00 47.00 53.00
1950 59.00 .00 51.00 57.00 47.00
1951 61.00 .00 56.00 53.00 57.00
1952 38.00 .00 41.00 39.00 47.00
1953 61.00 .00 46.00 44.00 50.00
1954 49.00 .00 71.00 63.00 55.00
1955 73.00 .00 66.00 73.00 69.00
1956 44.00 .00 42.00 39.00 26.00
1957 42.00 .00 32.00 37.00 33.00
1958 39.00 .00 46.00 42.00 56.00
1959 55.00 .00 41.00 63.00 58.00
1960 52.00 .00 51.00 48.00 44.00
1961 45.00 .00 61.00 50.00 58.00
1962 61.00 .00 66.00 47.00 69.00
1963 39.00 .00 46.00 44.00 34.00
1964 41.00 .00 36.00 34.00 36.00
1965 50.00 .00 61.00 50.00 36.00
1966 40.00 .00 26.00 44.00 50.00
1967 60.00 .00 66.00 60.00 55.00
1968 47.00 .00 26.00 47.00 42.00
1969 59.00 .00 44.00 63.00 65.00
1970 49.00 .00 36.00 50.00 44.00
1971 46.00 .00 51.00 44.00 39.00
1972 58.00 .00 61.00 60.00 58.00
1973 71.00 .00 66.00 73.00 63.00
1974 58.00 .00 66.00 68.00 74.00
1975 46.00 .00 51.00 55.00 58.00
1976 43.00 .00 31.00 47.00 45.00
1977 54.00 .00 61.00 55.00 49.00
1978 56.00 .00 66.00 68.00 63.00
1979 46.00 .00 46.00 31.00 39.00
1980 54.00 .00 56.00 47.00 42.00
1981 57.00 .00 56.00 63.00 55.00
1982 54.00 .00 36.00 36.00 61.00
1983 71.00 .00 56.00 68.00 66.00
1984 48.00 .00 56.00 63.00 63.00
1985 40.00 .00 41.00 55.00 44.00
1986 64.00 .00 66.00 55.00 63.00
1987 51.00 .00 56.00 52.00 53.00
1988 39.00 .00 56.00 34.00 42.00
1989 40.00 .00 31.00 50.00 34.00
1990 61.00 .00 56.00 55.00 61.00
1991 66.00 .00 46.00 52.00 47.00
1992 49.00 .00 46.00 63.00 66.00
1993 65.00 1.00 61.00 68.00 69.00
1994 52.00 1.00 48.00 39.00 44.00
1995 46.00 1.00 51.00 44.00 47.00
1996 61.00 1.00 51.00 50.00 63.00
1997 72.00 1.00 56.00 71.00 66.00
1998 71.00 1.00 71.00 63.00 69.00
1999 40.00 1.00 41.00 34.00 39.00
2000 69.00 1.00 61.00 63.00 61.00
2001 64.00 1.00 66.00 68.00 69.00
2002 56.00 1.00 61.00 47.00 66.00
2003 49.00 1.00 41.00 47.00 33.00
2004 54.00 1.00 51.00 63.00 50.00
2005 53.00 1.00 51.00 52.00 61.00
2006 66.00 1.00 56.00 55.00 42.00
2007 67.00 1.00 56.00 60.00 50.00
2008 40.00 1.00 33.00 35.00 51.00
2009 46.00 1.00 56.00 47.00 50.00
2010 69.00 1.00 71.00 71.00 58.00
2011 40.00 1.00 56.00 57.00 61.00
2012 41.00 1.00 51.00 44.00 39.00
2013 57.00 1.00 66.00 65.00 46.00
2014 58.00 1.00 56.00 68.00 59.00
2015 57.00 1.00 66.00 73.00 55.00
2016 37.00 1.00 41.00 36.00 42.00
2017 55.00 1.00 46.00 43.00 55.00
2018 62.00 1.00 66.00 73.00 58.00
2019 64.00 1.00 56.00 52.00 58.00
2020 40.00 1.00 51.00 41.00 39.00
2021 50.00 1.00 51.00 60.00 50.00
2022 46.00 1.00 56.00 50.00 50.00
2023 53.00 1.00 56.00 50.00 39.00
2024 52.00 1.00 46.00 47.00 48.00
2025 45.00 1.00 46.00 47.00 34.00
2026 56.00 1.00 61.00 55.00 58.00
2027 45.00 1.00 56.00 50.00 44.00
2028 54.00 1.00 41.00 39.00 50.00
2029 56.00 1.00 46.00 50.00 47.00
2030 41.00 1.00 26.00 34.00 29.00
2031 54.00 1.00 56.00 57.00 50.00
2032 72.00 1.00 56.00 57.00 54.00
2033 56.00 1.00 51.00 68.00 50.00
2034 47.00 1.00 46.00 42.00 47.00
2035 49.00 1.00 66.00 61.00 44.00
2036 60.00 1.00 66.00 76.00 67.00
2037 54.00 1.00 46.00 47.00 58.00
2038 55.00 1.00 56.00 46.00 44.00
2039 33.00 1.00 41.00 39.00 42.00
2040 49.00 1.00 61.00 52.00 44.00
2041 43.00 1.00 51.00 28.00 44.00
2042 50.00 1.00 52.00 42.00 50.00
2043 52.00 1.00 51.00 47.00 39.00
2044 48.00 1.00 41.00 47.00 44.00
2045 58.00 1.00 66.00 52.00 53.00
2046 43.00 1.00 61.00 47.00 48.00
2047 41.00 1.00 31.00 50.00 55.00
2048 43.00 1.00 51.00 44.00 44.00
2049 46.00 1.00 41.00 47.00 40.00
2050 44.00 1.00 41.00 45.00 34.00
2051 43.00 1.00 46.00 47.00 42.00
2052 61.00 1.00 56.00 65.00 58.00
2053 40.00 1.00 51.00 43.00 50.00
2054 49.00 1.00 61.00 47.00 53.00
2055 56.00 1.00 66.00 57.00 58.00
2056 61.00 1.00 71.00 68.00 55.00
2057 50.00 1.00 61.00 52.00 54.00
2058 51.00 1.00 61.00 42.00 47.00
2059 42.00 1.00 41.00 42.00 42.00
2060 67.00 1.00 66.00 66.00 61.00
2061 53.00 1.00 61.00 47.00 53.00
2062 50.00 1.00 58.00 57.00 51.00
2063 51.00 1.00 31.00 47.00 63.00
2064 72.00 1.00 61.00 57.00 61.00
2065 48.00 1.00 61.00 52.00 55.00
2066 40.00 1.00 31.00 44.00 40.00
2067 53.00 1.00 61.00 50.00 61.00
2068 39.00 1.00 36.00 39.00 47.00
2069 63.00 1.00 41.00 57.00 55.00
2070 51.00 1.00 37.00 57.00 53.00
2071 45.00 1.00 43.00 42.00 50.00
2072 39.00 1.00 61.00 47.00 47.00
2073 42.00 1.00 39.00 42.00 31.00
2074 62.00 1.00 51.00 60.00 61.00
2075 44.00 1.00 51.00 44.00 35.00
2076 65.00 1.00 66.00 63.00 54.00
2077 63.00 1.00 71.00 65.00 55.00
2078 54.00 1.00 41.00 39.00 53.00
2079 45.00 1.00 36.00 50.00 58.00
2080 60.00 1.00 51.00 52.00 56.00
2081 49.00 1.00 51.00 60.00 50.00
2082 48.00 1.00 51.00 44.00 39.00
2083 57.00 1.00 61.00 52.00 63.00
2084 55.00 1.00 61.00 55.00 50.00
2085 66.00 1.00 56.00 50.00 66.00
2086 64.00 1.00 71.00 65.00 58.00
2087 55.00 1.00 51.00 52.00 53.00
2088 42.00 1.00 36.00 47.00 42.00
2089 56.00 1.00 61.00 63.00 55.00
2090 53.00 1.00 66.00 50.00 53.00
2091 41.00 1.00 41.00 42.00 42.00
2092 42.00 1.00 41.00 36.00 50.00
2093 53.00 1.00 56.00 50.00 55.00
2094 42.00 1.00 51.00 41.00 34.00
2095 60.00 1.00 56.00 47.00 50.00
2096 52.00 1.00 56.00 55.00 42.00
2097 38.00 1.00 46.00 42.00 36.00
2098 57.00 1.00 52.00 57.00 55.00
2099 58.00 1.00 61.00 55.00 58.00
2100 65.00 1.00 61.00 63.00 53.00
2104 /variables = math female socst read
2105 /statistics = coeff r anova ci (95)
2106 /dependent = science
2110 AT_CHECK([pspp -O format=csv conf.sps], [0], [dnl
2111 Table: Model Summary (science)
2112 ,R,R Square,Adjusted R Square,Std. Error of the Estimate
2113 ,.699,.489,.479,7.148
2115 Table: ANOVA (science)
2116 ,,Sum of Squares,df,Mean Square,F,Sig.
2117 ,Regression,9543.721,4,2385.930,46.695,.000
2118 ,Residual,9963.779,195,51.096,,
2119 ,Total,19507.500,199,,,
2121 Table: Coefficients (science)
2122 ,,Unstandardized Coefficients,,Standardized Coefficients,,,95% Confidence Interval for B,
2123 ,,B,Std. Error,Beta,t,Sig.,Lower Bound,Upper Bound
2124 ,(Constant),12.325,3.194,.000,3.859,.000,6.027,18.624
2125 ,math,.389,.074,.368,5.252,.000,.243,.535
2126 ,female,-2.010,1.023,-.101,-1.965,.051,-4.027,.007
2127 ,socst,.050,.062,.054,.801,.424,-.073,.173
2128 ,read,.335,.073,.347,4.607,.000,.192,.479
2135 dnl Checks for regression against bug #44877.
2136 AT_SETUP([LINEAR REGRESSION crash with long string variables])
2137 AT_DATA([regression.sps], [dnl
2140 DATA LIST notable LIST /text (A24) Y * X1 *
2142 V00276601 0.00 90.00
2143 V00292909 10.00 30.00
2144 V00291204 20.00 20.00
2145 V00300070 0.00 90.00
2152 /STATISTICS=COEFF R ANOVA
2157 AT_CHECK([pspp -o pspp.csv regression.sps])
2158 AT_CHECK([cat pspp.csv], [0], [dnl
2159 Table: Model Summary (X1)
2160 ,R,R Square,Adjusted R Square,Std. Error of the Estimate
2164 ,,Sum of Squares,df,Mean Square,F,Sig.
2165 ,Regression,3820.45,1,3820.45,16.81,.055
2166 ,Residual,454.55,2,227.27,,
2169 Table: Coefficients (X1)
2170 ,,Unstandardized Coefficients,,Standardized Coefficients,,
2171 ,,B,Std. Error,Beta,t,Sig.
2172 ,(Constant),85.45,10.16,.00,8.41,.004
2173 ,Y,-3.73,.91,-.95,-4.10,.055
2177 V00276601 ,.00,90.00,4.55
2178 V00292909 ,10.00,30.00,-18.18
2179 V00291204 ,20.00,20.00,9.09
2180 V00300070 ,.00,90.00,4.55
2185 dnl Test for a crash which happened on bad input syntax
2186 AT_SETUP([LINEAR REGRESSION -- Empty Parentheses])
2188 AT_DATA([empty-parens.sps], [dnl
2191 data list notable list /math female socst read science *
2193 58.00 1.00 61.00 55.00 58.00
2194 65.00 1.00 61.00 63.00 53.00
2198 /variables = math female socst read
2199 /statistics = coeff r anova ci ()
2200 /dependent = science
2204 AT_CHECK([pspp -o pspp.csv empty-parens.sps], [1], [ignore])