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.
8 0.65377128 7.735648 -23.97588
9 -0.13087553 6.142625 -19.63854
10 0.34880368 7.651430 -25.26557
11 0.69249021 6.125125 -16.57090
12 -0.07368178 8.245789 -25.80001
13 -0.34404919 6.031540 -17.56743
14 0.75981559 9.832291 -28.35977
15 -0.46958313 5.343832 -16.79548
16 -0.06108490 8.838262 -29.25689
17 0.56154863 6.200189 -18.58219
19 regression /variables=v0 v1 v2 /statistics defaults /dependent=v2 /method=enter /save=pred resid.
23 AT_CHECK([pspp -O format=csv regression.sps], [0], [dnl
24 Table: Model Summary (v2)
25 ,R,R Square,Adjusted R Square,Std. Error of the Estimate
29 ,,Sum of Squares,df,Mean Square,F,Significance
30 ,Regression,202.753,2,101.376,56.754,.000
31 ,Residual,12.504,7,1.786,,
34 Table: Coefficients (v2)
35 ,,B,Std. Error,Beta,t,Significance
36 ,(Constant),2.191,2.357,.000,.930,.380
37 ,v0,1.813,1.053,.171,1.722,.129
38 ,v1,-3.427,.332,-1.026,-10.334,.000
43 .654,7.736,-23.976,-.84,-23.13
44 -.131,6.143,-19.639,-.54,-19.10
45 .349,7.651,-25.266,-1.87,-23.40
46 .692,6.125,-16.571,.97,-17.54
47 -.074,8.246,-25.800,.40,-26.20
48 -.344,6.032,-17.567,1.53,-19.10
49 .760,9.832,-28.360,1.77,-30.13
50 -.470,5.344,-16.795,.18,-16.97
51 -.061,8.838,-29.257,-1.05,-28.21
52 .562,6.200,-18.582,-.54,-18.04
57 # Test to ensure that the /SAVE subcommand works properly when SPLIT is active
58 AT_SETUP([LINEAR REGRESSION - SAVE vs SPLITS])
60 # Generate some test data based on a linear model
61 AT_DATA([gen-data.sps], [dnl
65 compute x0 = rv.normal (0,1).
66 compute x1 = rv.normal (0,2).
67 compute err = rv.normal (0,0.1).
68 compute y = 4 - 2 * x0 + 3 * x1 + err.
69 compute g = (#c > 10).
75 print outfile='regdata.txt' /g x0 x1 y err *.
79 AT_CHECK([pspp -O format=csv gen-data.sps], [0], [ignore])
81 # Use our test data to create a predictor and a residual variable
83 AT_DATA([regression0.sps], [dnl
84 data list notable file='regdata.txt' list /g x0 x1 y err *.
95 print outfile='outdata-g0.txt' /g x0 x1 y err res1 pred1 *.
100 AT_CHECK([pspp -O format=csv regression0.sps], [0], [ignore])
102 # Use our test data to create a predictor and a residual variable
104 AT_DATA([regression1.sps], [dnl
105 data list notable file='regdata.txt' list /g x0 x1 y err *.
116 print outfile='outdata-g1.txt' /g x0 x1 y err res1 pred1 *.
121 AT_CHECK([pspp -O format=csv regression1.sps], [0], [ignore])
123 # Use our test data to create a predictor and a residual variable
124 # The data is split on G
125 AT_DATA([regression-split.sps], [dnl
126 data list notable file='regdata.txt' list /g x0 x1 y err *.
137 print outfile='outdata-split.txt' /g x0 x1 y err res1 pred1 *.
141 AT_CHECK([pspp -O format=csv regression-split.sps], [0], [ignore])
143 # The concatenation of G==0 and G==1 should be identical to the SPLIT data
144 AT_CHECK([cat outdata-g0.txt outdata-g1.txt | diff outdata-split.txt - ], [0], [])
149 # Test that the procedure behaves sensibly when presented with
150 # multiple dependent variables
151 AT_SETUP([LINEAR REGRESSION multiple dependent variables])
152 AT_DATA([regression.sps], [dnl
156 compute x0 = rv.normal (0, 1).
157 compute x1 = rv.normal (0, 2).
158 compute err = rv.normal (0, 0.8).
159 compute y = 2 - 1.5 * x0 + 8.4 * x1 + err.
172 AT_CHECK([pspp -O format=csv regression.sps > output], [0], [ignore])
175 AT_CHECK([head -16 output > first], [0], [])
176 AT_CHECK([tail -16 output > second], [0], [])
178 AT_CHECK([sed -e 's/ycopy/y/g' second | diff first -], [0], [])
183 # Tests the QR decomposition used by the REGRESSION command.
184 AT_SETUP([LINEAR REGRESSION test of QR decomposition])
185 AT_DATA([regression.sps], [dnl
186 data list list / v0 to v1.
188 -12.84099361 0.873270778
189 16.64932538 0.371315664
190 -1.88061907 0.505503722
191 -6.20952354 0.734698282
192 0.33272576 0.891224610
193 -5.54912717 0.052318165
194 6.11832417 0.448853404
195 11.78124974 0.470447593
196 0.75960353 0.565082303
197 6.06432768 0.149316743
198 -2.64919436 0.752532411
199 -10.32250712 0.798263603
200 2.06355038 0.469129797
201 -9.71851742 0.927162270
202 4.65582553 0.250629262
203 9.54574474 0.847032310
204 7.35544368 0.197028541
205 -2.09609740 0.400584261
206 10.30101161 0.671546480
207 -5.24501039 0.929962876
208 1.73412473 0.758161354
209 -3.12732732 0.569785505
210 12.66261501 0.630640223
211 -2.90956805 0.576067804
212 4.89649177 0.624483995
213 13.64613114 0.591089881
214 14.03198397 0.544587572
215 2.23566810 0.967898139
216 5.37367760 0.916246929
217 9.01346888 0.451702743
218 0.75378683 0.235544137
219 -3.47470624 0.742668194
220 -1.02063266 0.860311687
221 -2.67132813 0.082460702
222 23.67661680 0.932553932
223 7.95061359 0.430161125
224 2.05300558 0.066331375
225 -2.01332644 0.163705417
226 20.00663784 0.587292630
227 3.06099417 0.161411889
228 -3.46115358 0.216684625
229 -6.85287183 0.548714855
230 -4.27923809 0.630997663
231 -0.94863395 0.880612945
232 4.47481747 0.359885215
233 -12.80962955 0.886070341
234 9.35753086 0.187176558
235 2.81002235 0.063035095
236 0.01532424 0.964327101
237 0.29867732 0.866408063
238 -2.89035649 0.812135868
239 4.17352811 0.608884061
240 18.15502183 0.920568258
241 -2.92662792 0.550792959
242 -6.08090449 0.965036595
243 -1.09135397 0.862548019
244 7.02816784 0.042277017
245 -21.20245068 0.430673493
246 -8.83397584 0.724976162
247 -0.89055843 0.017934904
248 7.03871587 0.308829557
249 3.84286316 0.685105924
250 4.50280692 0.447635420
251 11.39207346 0.875177896
252 10.86673874 0.518530912
253 7.09853081 0.588367569
254 -12.82864915 0.184667098
255 13.74888760 0.610891139
256 0.37379146 0.557720134
257 -9.79020267 0.942839981
258 0.71574466 0.564570338
259 -17.56040637 0.182061777
260 2.52620466 0.306875011
261 5.37718673 0.366807049
262 -1.83964300 0.465772898
263 6.04848363 0.644501799
264 4.57402403 0.121419591
265 8.55606848 0.373011464
266 -8.46827907 0.491176571
267 -1.77989798 0.734722847
268 -0.68661121 0.540984182
269 1.55798880 0.822587656
270 5.22810831 0.333747878
271 9.50280477 0.068100934
272 -3.74521465 0.248537644
273 1.36045068 0.851827791
274 4.41604088 0.197207162
275 -3.72568327 0.726916693
276 -5.36123334 0.906513529
277 3.61594583 0.414340595
278 -10.01952852 0.140372658
279 25.48681482 0.354309660
280 -3.34529093 0.090075388
281 -18.00437582 0.461438059
282 -5.29782460 0.004362856
283 2.79608522 0.861294398
284 -1.64076209 0.345775481
285 6.82802334 0.137933862
286 -0.45416818 0.404379208
287 -1.66868582 0.797685201
288 -10.02820292 0.075876582
289 5.68232031 0.404815042
290 8.25113850 0.769173748
291 -2.83544237 0.076583474
292 0.87659945 0.092751009
293 6.60270870 0.530444351
294 -12.63924989 0.362099960
295 -6.24451253 0.641993458
296 3.53339015 0.461991892
297 -0.74012232 0.437409755
298 15.37311996 0.974913038
299 -8.09464797 0.543308711
300 -9.61320222 0.221564578
301 0.21843662 0.856512540
302 -1.56958954 0.610709221
303 6.44977372 0.200382138
304 -13.29136274 0.093222309
305 6.46257214 0.024135196
306 -3.82727990 0.601335801
307 0.43081953 0.268230667
308 19.06654416 0.219972815
309 17.02906651 0.996849502
310 -10.18073139 0.012543080
311 12.72088788 0.910600764
312 10.45328185 0.331285901
313 7.14370922 0.896312020
314 -2.81754334 0.048741266
315 6.40217095 0.075796756
316 -3.18030478 0.666325307
317 8.64585957 0.120549153
318 1.37952764 0.899991932
319 -11.81143886 0.601949630
320 0.03899706 0.363808260
321 -10.63828243 0.031092967
322 -6.66940972 0.246204205
323 -5.07374962 0.951272057
324 4.82281566 0.063928187
325 -21.93693564 0.050972680
326 -4.54569883 0.225839693
327 -0.92422779 0.437796785
328 -1.11683029 0.740215139
329 16.77765554 0.851072372
330 9.73614597 0.388180586
331 14.05345168 0.063760129
332 1.20512012 0.665964184
333 8.00307080 0.102447114
334 8.01252623 0.580929209
335 -13.54924183 0.438420739
336 9.87164361 0.970859344
337 17.63437095 0.250501797
338 -3.42503574 0.873290220
339 -2.45873197 0.847756049
340 17.29212092 0.411683187
341 1.15496098 0.530658504
342 -2.14438907 0.592255367
343 -1.79942021 0.517773009
344 -1.30677990 0.830860762
345 1.70233874 0.291826660
346 -3.05532536 0.801767829
347 -4.06732625 0.092294501
348 6.34665476 0.270426235
349 9.46946411 0.196915311
350 14.50919907 0.480357167
351 8.93767237 0.778228613
352 1.90298854 0.903146151
353 18.50500507 0.598561307
354 4.45123027 0.555898218
355 11.37344114 0.616557707
356 -12.14693218 0.409187285
357 18.27198688 0.141619222
358 -5.75939569 0.056989619
359 -4.05515382 0.369281201
360 16.69882098 0.946885257
361 6.39050536 0.679704228
362 4.04213339 0.662792380
363 6.89608366 0.419877433
364 1.56496633 0.358227958
365 5.16679947 0.095144366
366 -3.06280456 0.883265975
367 2.76279175 0.866571973
368 1.84969249 0.264869828
369 21.79840498 0.702650979
370 1.42450528 0.719308635
371 0.96797046 0.111937435
372 18.26840323 0.075621738
373 13.38288377 0.573399086
374 2.41101500 0.766238677
375 3.83866337 0.499888953
376 -1.56577367 0.695244089
377 -0.90342790 0.671654151
378 10.83775583 0.026041124
379 -9.89767935 0.745297991
380 11.74840150 0.309144074
381 1.73069359 0.814063985
382 -5.27966183 0.591005828
383 3.33030043 0.559401806
384 1.31427975 0.520950237
385 -10.04588558 0.507008362
386 10.41228345 0.425867272
387 1.71961097 0.595783108
388 -17.54904427 0.328788939
389 -2.23545419 0.223377350
390 -8.68774333 0.980964240
391 -3.48048220 0.008877675
392 -3.69635326 0.090236718
393 9.76114237 0.769375983
394 -10.25662038 0.508137553
395 0.11155446 0.468504431
396 -8.06824580 0.414098962
397 3.10031660 0.327130207
398 -3.33393146 0.756896774
399 -3.96276749 0.530956360
400 14.53610268 0.846474699
401 1.70505918 0.754662464
402 -1.93495001 0.656650411
403 5.01974522 0.745337633
404 13.41249973 0.489362476
405 11.49288744 0.335924476
406 12.59019763 0.155560469
407 -10.17947298 0.677318449
408 0.05556115 0.655090105
409 3.82092860 0.051838719
410 8.23041456 0.918272190
411 -0.50314649 0.772015826
412 20.05162157 0.880265258
413 8.98816884 0.666646668
414 -6.28312120 0.138534416
415 3.68589909 0.274559458
416 0.59699510 0.253180863
417 -2.74783135 0.983525221
418 0.32515065 0.839969577
419 -3.60606166 0.330646732
420 -0.82037740 0.129591173
421 6.12444860 0.098536516
422 10.95671074 0.033546728
423 -2.84911174 0.720288722
424 6.04597572 0.577061422
425 -0.60147150 0.674096868
426 -5.30458364 0.291468008
427 2.68044943 0.379853840
428 0.85986585 0.984214339
429 -12.77906359 0.882390290
430 7.21420144 0.550884826
431 2.31817022 0.231021556
432 11.60161950 0.888496654
433 -0.19346228 0.242609713
434 5.07478120 0.759161318
435 14.54155003 0.040387654
436 3.81039636 0.874572741
437 2.23233049 0.448317248
438 0.19481869 0.201906051
439 2.81530451 0.132131690
440 12.39893259 0.674693704
441 0.47054642 0.632959494
442 2.16152913 0.734480632
443 0.33398836 0.315024718
444 7.35509037 0.304570986
445 -2.92336559 0.539062343
446 5.79622573 0.392393310
447 -2.37607425 0.403380474
448 0.04498550 0.756875541
449 -1.63674414 0.613789514
450 11.80310547 0.832651469
451 6.30630243 0.850689403
452 1.48394652 0.096243229
453 4.03361865 0.799660045
454 3.54707273 0.408520520
455 2.00327040 0.702944912
456 17.30761707 0.380542812
457 5.72738968 0.105447516
458 -13.64604891 0.328506659
459 8.35976334 0.702173924
460 -7.41197443 0.134396488
461 -15.95683040 0.618526462
462 8.76889573 0.950243069
463 -1.13482624 0.113477080
464 -0.60311407 0.090444247
465 4.95508365 0.612511543
466 5.36934491 0.979213258
467 -0.03554882 0.807185690
468 -11.58131144 0.183341373
469 4.46809041 0.796330582
470 12.49741067 0.346860912
471 8.63824488 0.073684997
472 0.49990913 0.732519306
473 12.82688360 0.109400213
474 13.20375065 0.850369092
475 -8.41110869 0.177717087
476 16.31959963 0.727704840
477 17.59203613 0.235311681
478 0.32148420 0.842195936
479 5.43148331 0.670904647
480 7.14649727 0.028190029
481 0.25410683 0.421535783
482 -12.41047826 0.086404379
483 -10.64180909 0.229659236
484 -6.40185653 0.876365242
485 15.63063324 0.667672536
486 1.94280423 0.799266628
487 -5.76507450 0.367344192
488 8.60895533 0.154109357
489 9.38306751 0.788742770
490 3.43573528 0.284535277
491 4.81848966 0.872283177
492 11.65839314 0.234109111
493 -5.57884822 0.030363060
494 -3.94238060 0.325320686
495 9.38133340 0.201141788
496 -7.65003459 0.647734396
497 11.23091019 0.084927159
498 -6.07705432 0.037273791
499 7.46380750 0.506897136
500 7.42034855 0.869351148
501 -4.43031973 0.231191152
502 -1.07351537 0.480234836
503 -1.40653281 0.690620421
504 -3.82710168 0.990191328
505 5.04583490 0.543427375
506 -11.54265099 0.270542185
507 0.49059479 0.991447248
508 -1.40871469 0.555998766
509 3.64241437 0.743840673
510 -18.30031589 0.357478210
511 4.27487959 0.770619738
512 1.28805821 0.654787106
513 -3.19542768 0.218110139
514 12.53375654 0.011857644
515 11.78889419 0.054127726
516 -5.38392310 0.839309080
517 16.38024181 0.228801038
518 -0.59622631 0.134381782
519 -0.74107258 0.258146632
520 -12.31429450 0.020524447
521 -0.79785028 0.968028764
522 6.39899711 0.038162566
523 7.42024044 0.716163692
524 -3.62470664 0.018201813
525 -2.55049724 0.162446610
526 -10.79888854 0.683070478
527 10.18490144 0.546461234
528 -2.76979044 0.198830067
529 4.85164813 0.094100357
530 0.96477200 0.381801756
531 8.13344336 0.639730450
532 9.04684412 0.786084368
533 10.41746272 0.828304181
534 0.94334368 0.798419831
535 10.13116556 0.191715972
536 -4.12728628 0.575178239
537 -9.59222379 0.876405375
538 1.64680258 0.391003085
539 -4.58897613 0.039176486
540 0.38394379 0.511577564
541 -4.80428215 0.222785463
542 0.35363661 0.681658725
543 -9.63685708 0.183035382
544 3.54363414 0.766127414
545 6.89610808 0.967514568
546 -2.03781105 0.464416752
547 8.67956196 0.421424078
548 -1.09959038 0.061231448
549 7.12587456 0.028601318
550 -6.93064672 0.402561175
551 8.57989199 0.925089270
552 -9.55071810 0.454993099
553 -8.11914736 0.509644286
554 -5.41909698 0.077813151
555 -17.03336572 0.875713545
556 -1.27438609 0.602163625
557 3.09834374 0.105599007
558 -1.59865741 0.439939102
559 11.82272089 0.754984309
560 4.30969696 0.483834579
561 -10.76886192 0.222486992
562 7.05419803 0.903020271
563 7.36096847 0.440357053
564 -2.05864869 0.581170147
565 -9.08366913 0.318677911
566 8.57119930 0.605668919
567 7.87702340 0.570206991
568 5.22035786 0.542344385
569 2.37238850 0.595969470
570 -4.29809941 0.634313781
571 4.51647479 0.796663089
572 -0.62478780 0.562099444
573 8.50866078 0.490014249
574 3.46694991 0.122890089
575 -7.31956453 0.885170890
576 2.20259268 0.167180856
577 -1.81003626 0.702563515
578 8.44526939 0.973495019
579 8.19767069 0.881261264
580 -5.92422578 0.686557351
581 -0.11826129 0.712798344
582 5.66132869 0.922826429
583 -5.40845018 0.642183516
584 6.67839036 0.680978989
585 11.88962825 0.487904896
586 3.32266332 0.931709581
587 0.24234019 0.405641313
588 -12.79023339 0.361005489
589 -13.57875491 0.266289733
590 1.81304596 0.775093821
591 0.36755600 0.400225605
592 -9.15574205 0.518040748
593 -3.90436548 0.396869908
594 9.24764042 0.669374848
595 0.74869385 0.609881390
596 -3.62958907 0.928867495
597 -0.02527232 0.557679930
598 0.04433418 0.152565816
599 11.76152632 0.865663501
600 -4.62181124 0.007000650
601 5.82271403 0.389678502
602 0.33289002 0.532940826
603 -7.65647076 0.681574524
604 11.81023732 0.107165912
605 11.42121999 0.989580324
606 -5.47120641 0.762285550
607 3.82311561 0.388755074
608 16.91059711 0.461236022
609 4.14012105 0.802420151
610 -1.35278659 0.036646959
611 -12.81733350 0.179096148
612 -0.94395134 0.450959878
613 -5.39002376 0.264783062
614 4.16227017 0.780743762
615 7.26179625 0.821382454
616 15.10062276 0.469253936
617 1.45877225 0.685434405
618 -9.87966760 0.767201511
619 7.03156071 0.195142483
620 -11.71327419 0.774014869
621 -4.55518706 0.973103604
622 -1.75221406 0.175172193
623 10.35631400 0.080670414
624 4.97650495 0.597478189
625 2.25703939 0.585949751
626 10.72500409 0.339720931
627 -5.02901029 0.997874377
628 6.24398637 0.655067479
629 -5.83880059 0.184948259
630 2.17256077 0.746741866
631 -5.59809380 0.277523381
632 8.19384177 0.334565607
633 3.35250431 0.952057263
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1686 -7.70962391 0.711708342
1687 -2.46291902 0.390902746
1689 regression /variables=v0 v1 /statistics defaults /dependent=v0 /method=enter.
1691 AT_CHECK([pspp -o pspp.csv regression.sps])
1692 AT_CHECK([cat pspp.csv], [0], [dnl
1693 Table: Reading free-form data from INLINE.
1698 Table: Model Summary (v0)
1699 ,R,R Square,Adjusted R Square,Std. Error of the Estimate
1703 ,,Sum of Squares,df,Mean Square,F,Significance
1704 ,Regression,235.23,1,235.23,3.58,.06
1705 ,Residual,98438.40,1498,65.71,,
1706 ,Total,98673.63,1499,,,
1708 Table: Coefficients (v0)
1709 ,,B,Std. Error,Beta,t,Significance
1710 ,(Constant),1.24,.42,.00,2.95,.00
1711 ,v1,1.37,.72,.05,1.89,.06
1716 AT_SETUP([LINEAR REGRESSION no crash on all missing])
1717 AT_DATA([regcrash.sps], [dnl
1718 data list list /x * y.
1733 regression /variables=x y /dependent=y.
1736 AT_CHECK([pspp -o pspp.csv regcrash.sps], [1], [ignore], [ignore])
1742 AT_SETUP([LINEAR REGRESSION missing dependent variable])
1744 dnl Test for a bug where missing values in the dependent variable were not being
1745 dnl ignored like they should have been.
1746 AT_DATA([reg-mdv-ref.sps], [dnl
1747 data list notable list / v0 to v2.
1749 0.65377128 7.735648 -23.97588
1750 -0.13087553 6.142625 -19.63854
1751 0.34880368 7.651430 -25.26557
1752 0.69249021 6.125125 -16.57090
1753 -0.07368178 8.245789 -25.80001
1754 -0.34404919 6.031540 -17.56743
1755 0.75981559 9.832291 -28.35977
1756 -0.46958313 5.343832 -16.79548
1757 -0.06108490 8.838262 -29.25689
1758 0.56154863 6.200189 -18.58219
1760 regression /variables=v0 v1
1761 /statistics defaults
1766 AT_CHECK([pspp -o pspp-ref.csv reg-mdv-ref.sps])
1768 AT_DATA([reg-mdv.sps], [dnl
1769 data list notable list / v0 to v2.
1771 0.65377128 7.735648 -23.97588
1772 -0.13087553 6.142625 -19.63854
1773 0.34880368 7.651430 -25.26557
1774 0.69249021 6.125125 -16.57090
1775 -0.07368178 8.245789 -25.80001
1776 -0.34404919 6.031540 -17.56743
1777 0.75981559 9.832291 -28.35977
1778 -0.46958313 5.343832 -16.79548
1779 -0.06108490 8.838262 -29.25689
1780 0.56154863 6.200189 -18.58219
1784 missing values v2 (9).
1786 regression /variables=v0 v1
1787 /statistics defaults
1792 AT_CHECK([pspp -o pspp.csv reg-mdv.sps])
1794 AT_CHECK([diff pspp.csv pspp-ref.csv])
1799 AT_SETUP([LINEAR REGRESSION with invalid syntax (and empty dataset)])
1801 AT_DATA([ss.sps], [dnl
1802 data list notable list / v0 to v2.
1806 regression /variables=v0 v1
1807 /statistics r coeff anova
1812 AT_CHECK([pspp ss.sps], [1], [ignore])