+++ /dev/null
-dnl PSPP - a program for statistical analysis.
-dnl Copyright (C) 2017 Free Software Foundation, Inc.
-dnl
-dnl This program is free software: you can redistribute it and/or modify
-dnl it under the terms of the GNU General Public License as published by
-dnl the Free Software Foundation, either version 3 of the License, or
-dnl (at your option) any later version.
-dnl
-dnl This program is distributed in the hope that it will be useful,
-dnl but WITHOUT ANY WARRANTY; without even the implied warranty of
-dnl MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
-dnl GNU General Public License for more details.
-dnl
-dnl You should have received a copy of the GNU General Public License
-dnl along with this program. If not, see <http://www.gnu.org/licenses/>.
-dnl
-AT_BANNER([LINEAR REGRESSION])
-
-AT_SETUP([LINEAR REGRESSION - basic])
-AT_DATA([regression.sps], [dnl
-set format = F22.3.
-data list notable list / v0 to v2.
-filter by v0.
-begin data
- 0.65377128 7.735648 -23.97588
--0.13087553 6.142625 -19.63854
- 0.34880368 7.651430 -25.26557
- 0.69249021 6.125125 -16.57090
--0.07368178 8.245789 -25.80001
--0.34404919 6.031540 -17.56743
- 0.75981559 9.832291 -28.35977
--0.46958313 5.343832 -16.79548
--0.06108490 8.838262 -29.25689
- 0.56154863 6.200189 -18.58219
-end data
-regression /variables=v0 v1 v2 /statistics defaults /dependent=v2 /method=enter /save=pred resid.
-list.
-])
-
-AT_CHECK([pspp -O format=csv regression.sps], [0], [dnl
-"regression.sps:16.82-16.96: warning: REGRESSION: REGRESSION with SAVE ignores FILTER. All cases will be processed.
- 16 | regression /variables=v0 v1 v2 /statistics defaults /dependent=v2 /method=enter /save=pred resid.
- | ^~~~~~~~~~~~~~~"
-
-Table: Model Summary (v2)
-R,R Square,Adjusted R Square,Std. Error of the Estimate
-.971,.942,.925,1.337
-
-Table: ANOVA (v2)
-,Sum of Squares,df,Mean Square,F,Sig.
-Regression,202.753,2,101.376,56.754,.000
-Residual,12.504,7,1.786,,
-Total,215.256,9,,,
-
-Table: Coefficients (v2)
-,Unstandardized Coefficients,,Standardized Coefficients,t,Sig.
-,B,Std. Error,Beta,,
-(Constant),2.191,2.357,.000,.930,.380
-v0,1.813,1.053,.171,1.722,.129
-v1,-3.427,.332,-1.026,-10.334,.000
-
-Table: Data List
-v0,v1,v2,RES1,PRED1
-.654,7.736,-23.976,-.84,-23.13
--.131,6.143,-19.639,-.54,-19.10
-.349,7.651,-25.266,-1.87,-23.40
-.692,6.125,-16.571,.97,-17.54
--.074,8.246,-25.800,.40,-26.20
--.344,6.032,-17.567,1.53,-19.10
-.760,9.832,-28.360,1.77,-30.13
--.470,5.344,-16.795,.18,-16.97
--.061,8.838,-29.257,-1.05,-28.21
-.562,6.200,-18.582,-.54,-18.04
-])
-AT_CLEANUP
-
-
-AT_SETUP([LINEAR REGRESSION - one save])
-AT_DATA([regression.sps], [dnl
-set format = F22.3.
-data list notable list / v0 to v2.
-begin data
- 0.65377128 7.735648 -23.97588
--0.13087553 6.142625 -19.63854
- 0.34880368 7.651430 -25.26557
- 0.69249021 6.125125 -16.57090
--0.07368178 8.245789 -25.80001
--0.34404919 6.031540 -17.56743
- 0.75981559 9.832291 -28.35977
--0.46958313 5.343832 -16.79548
--0.06108490 8.838262 -29.25689
- 0.56154863 6.200189 -18.58219
-end data
-regression /variables=v0 v1 v2 /statistics defaults /dependent=v2 /method=enter /save=resid.
-regression /variables=v0 v1 v2 /statistics defaults /dependent=v2 /method=enter /save=pred.
-list.
-])
-
-AT_CHECK([pspp -O format=csv regression.sps], [0], [dnl
-Table: Model Summary (v2)
-R,R Square,Adjusted R Square,Std. Error of the Estimate
-.971,.942,.925,1.337
-
-Table: ANOVA (v2)
-,Sum of Squares,df,Mean Square,F,Sig.
-Regression,202.753,2,101.376,56.754,.000
-Residual,12.504,7,1.786,,
-Total,215.256,9,,,
-
-Table: Coefficients (v2)
-,Unstandardized Coefficients,,Standardized Coefficients,t,Sig.
-,B,Std. Error,Beta,,
-(Constant),2.191,2.357,.000,.930,.380
-v0,1.813,1.053,.171,1.722,.129
-v1,-3.427,.332,-1.026,-10.334,.000
-
-Table: Model Summary (v2)
-R,R Square,Adjusted R Square,Std. Error of the Estimate
-.971,.942,.925,1.337
-
-Table: ANOVA (v2)
-,Sum of Squares,df,Mean Square,F,Sig.
-Regression,202.753,2,101.376,56.754,.000
-Residual,12.504,7,1.786,,
-Total,215.256,9,,,
-
-Table: Coefficients (v2)
-,Unstandardized Coefficients,,Standardized Coefficients,t,Sig.
-,B,Std. Error,Beta,,
-(Constant),2.191,2.357,.000,.930,.380
-v0,1.813,1.053,.171,1.722,.129
-v1,-3.427,.332,-1.026,-10.334,.000
-
-Table: Data List
-v0,v1,v2,RES1,PRED1
-.654,7.736,-23.976,-.84,-23.13
--.131,6.143,-19.639,-.54,-19.10
-.349,7.651,-25.266,-1.87,-23.40
-.692,6.125,-16.571,.97,-17.54
--.074,8.246,-25.800,.40,-26.20
--.344,6.032,-17.567,1.53,-19.10
-.760,9.832,-28.360,1.77,-30.13
--.470,5.344,-16.795,.18,-16.97
--.061,8.838,-29.257,-1.05,-28.21
-.562,6.200,-18.582,-.54,-18.04
-])
-AT_CLEANUP
-
-
-# Test to ensure that the /SAVE subcommand works properly when SPLIT is active
-AT_SETUP([LINEAR REGRESSION - SAVE vs SPLITS])
-
-# Generate some test data based on a linear model
-AT_DATA([gen-data.sps], [dnl
-set seed = 1.
-input program.
-loop #c = 1 to 20.
- compute x0 = rv.normal (0,1).
- compute x1 = rv.normal (0,2).
- compute err = rv.normal (0,0.1).
- compute y = 4 - 2 * x0 + 3 * x1 + err.
- compute g = (#c > 10).
- end case.
-end loop.
-end file.
-end input program.
-
-print outfile='regdata.txt' /g x0 x1 y err *.
-execute.
-])
-
-AT_CHECK([pspp -O format=csv gen-data.sps], [0], [ignore])
-
-# Use our test data to create a predictor and a residual variable
-# for G == 0
-AT_DATA([regression0.sps], [dnl
-data list notable file='regdata.txt' list /g x0 x1 y err *.
-
-select if (g = 0).
-
-regression
- /variables = x0 x1
- /dependent = y
- /statistics = all
- /save = pred resid.
- .
-
-print outfile='outdata-g0.txt' /g x0 x1 y err res1 pred1 *.
-execute.
-])
-
-
-AT_CHECK([pspp -O format=csv regression0.sps], [0], [ignore])
-
-# Use our test data to create a predictor and a residual variable
-# for G == 1
-AT_DATA([regression1.sps], [dnl
-data list notable file='regdata.txt' list /g x0 x1 y err *.
-
-select if (g = 1).
-
-regression
- /variables = x0 x1
- /dependent = y
- /statistics = all
- /save = pred resid.
- .
-
-print outfile='outdata-g1.txt' /g x0 x1 y err res1 pred1 *.
-execute.
-])
-
-
-AT_CHECK([pspp -O format=csv regression1.sps], [0], [ignore])
-
-# Use our test data to create a predictor and a residual variable
-# The data is split on G
-AT_DATA([regression-split.sps], [dnl
-data list notable file='regdata.txt' list /g x0 x1 y err *.
-
-split file by g.
-
-regression
- /variables = x0 x1
- /dependent = y
- /statistics = all
- /save = pred resid.
- .
-
-print outfile='outdata-split.txt' /g x0 x1 y err res1 pred1 *.
-execute.
-])
-
-AT_CHECK([pspp -O format=csv regression-split.sps], [0], [ignore])
-
-# The concatenation of G==0 and G==1 should be identical to the SPLIT data
-AT_CHECK([cat outdata-g0.txt outdata-g1.txt | diff outdata-split.txt - ], [0], [])
-
-AT_CLEANUP
-
-
-# Test that the procedure behaves sensibly when presented with
-# multiple dependent variables
-AT_SETUP([LINEAR REGRESSION multiple dependent variables])
-AT_DATA([regression.sps], [dnl
-set seed = 2.
-input program.
-loop #c = 1 to 200.
- compute x0 = rv.normal (0, 1).
- compute x1 = rv.normal (0, 2).
- compute err = rv.normal (0, 0.8).
- compute y = 2 - 1.5 * x0 + 8.4 * x1 + err.
- compute ycopy = y.
- end case.
-end loop.
-end file.
-end input program.
-
-regression
- /variables = x0 x1
- /dependent = y ycopy
- /statistics = default.
-])
-
-AT_CHECK([pspp -O format=csv regression.sps > output], [0], [ignore])
-
-AT_CHECK([head -16 output > first], [0], [])
-AT_CHECK([tail -16 output > second], [0], [])
-
-AT_CHECK([sed -e 's/ycopy/y/g' second | diff first -], [0], [])
-
-
-AT_CLEANUP
-
-# Tests the QR decomposition used by the REGRESSION command.
-AT_SETUP([LINEAR REGRESSION test of QR decomposition])
-AT_DATA([regression.sps], [dnl
-data list list / v0 to v1.
-begin data
--12.84099361 0.873270778
- 16.64932538 0.371315664
- -1.88061907 0.505503722
- -6.20952354 0.734698282
- 0.33272576 0.891224610
- -5.54912717 0.052318165
- 6.11832417 0.448853404
- 11.78124974 0.470447593
- 0.75960353 0.565082303
- 6.06432768 0.149316743
- -2.64919436 0.752532411
--10.32250712 0.798263603
- 2.06355038 0.469129797
- -9.71851742 0.927162270
- 4.65582553 0.250629262
- 9.54574474 0.847032310
- 7.35544368 0.197028541
- -2.09609740 0.400584261
- 10.30101161 0.671546480
- -5.24501039 0.929962876
- 1.73412473 0.758161354
- -3.12732732 0.569785505
- 12.66261501 0.630640223
- -2.90956805 0.576067804
- 4.89649177 0.624483995
- 13.64613114 0.591089881
- 14.03198397 0.544587572
- 2.23566810 0.967898139
- 5.37367760 0.916246929
- 9.01346888 0.451702743
- 0.75378683 0.235544137
- -3.47470624 0.742668194
- -1.02063266 0.860311687
- -2.67132813 0.082460702
- 23.67661680 0.932553932
- 7.95061359 0.430161125
- 2.05300558 0.066331375
- -2.01332644 0.163705417
- 20.00663784 0.587292630
- 3.06099417 0.161411889
- -3.46115358 0.216684625
- -6.85287183 0.548714855
- -4.27923809 0.630997663
- -0.94863395 0.880612945
- 4.47481747 0.359885215
--12.80962955 0.886070341
- 9.35753086 0.187176558
- 2.81002235 0.063035095
- 0.01532424 0.964327101
- 0.29867732 0.866408063
- -2.89035649 0.812135868
- 4.17352811 0.608884061
- 18.15502183 0.920568258
- -2.92662792 0.550792959
- -6.08090449 0.965036595
- -1.09135397 0.862548019
- 7.02816784 0.042277017
--21.20245068 0.430673493
- -8.83397584 0.724976162
- -0.89055843 0.017934904
- 7.03871587 0.308829557
- 3.84286316 0.685105924
- 4.50280692 0.447635420
- 11.39207346 0.875177896
- 10.86673874 0.518530912
- 7.09853081 0.588367569
--12.82864915 0.184667098
- 13.74888760 0.610891139
- 0.37379146 0.557720134
- -9.79020267 0.942839981
- 0.71574466 0.564570338
--17.56040637 0.182061777
- 2.52620466 0.306875011
- 5.37718673 0.366807049
- -1.83964300 0.465772898
- 6.04848363 0.644501799
- 4.57402403 0.121419591
- 8.55606848 0.373011464
- -8.46827907 0.491176571
- -1.77989798 0.734722847
- -0.68661121 0.540984182
- 1.55798880 0.822587656
- 5.22810831 0.333747878
- 9.50280477 0.068100934
- -3.74521465 0.248537644
- 1.36045068 0.851827791
- 4.41604088 0.197207162
- -3.72568327 0.726916693
- -5.36123334 0.906513529
- 3.61594583 0.414340595
--10.01952852 0.140372658
- 25.48681482 0.354309660
- -3.34529093 0.090075388
--18.00437582 0.461438059
- -5.29782460 0.004362856
- 2.79608522 0.861294398
- -1.64076209 0.345775481
- 6.82802334 0.137933862
- -0.45416818 0.404379208
- -1.66868582 0.797685201
--10.02820292 0.075876582
- 5.68232031 0.404815042
- 8.25113850 0.769173748
- -2.83544237 0.076583474
- 0.87659945 0.092751009
- 6.60270870 0.530444351
--12.63924989 0.362099960
- -6.24451253 0.641993458
- 3.53339015 0.461991892
- -0.74012232 0.437409755
- 15.37311996 0.974913038
- -8.09464797 0.543308711
- -9.61320222 0.221564578
- 0.21843662 0.856512540
- -1.56958954 0.610709221
- 6.44977372 0.200382138
--13.29136274 0.093222309
- 6.46257214 0.024135196
- -3.82727990 0.601335801
- 0.43081953 0.268230667
- 19.06654416 0.219972815
- 17.02906651 0.996849502
--10.18073139 0.012543080
- 12.72088788 0.910600764
- 10.45328185 0.331285901
- 7.14370922 0.896312020
- -2.81754334 0.048741266
- 6.40217095 0.075796756
- -3.18030478 0.666325307
- 8.64585957 0.120549153
- 1.37952764 0.899991932
--11.81143886 0.601949630
- 0.03899706 0.363808260
--10.63828243 0.031092967
- -6.66940972 0.246204205
- -5.07374962 0.951272057
- 4.82281566 0.063928187
--21.93693564 0.050972680
- -4.54569883 0.225839693
- -0.92422779 0.437796785
- -1.11683029 0.740215139
- 16.77765554 0.851072372
- 9.73614597 0.388180586
- 14.05345168 0.063760129
- 1.20512012 0.665964184
- 8.00307080 0.102447114
- 8.01252623 0.580929209
--13.54924183 0.438420739
- 9.87164361 0.970859344
- 17.63437095 0.250501797
- -3.42503574 0.873290220
- -2.45873197 0.847756049
- 17.29212092 0.411683187
- 1.15496098 0.530658504
- -2.14438907 0.592255367
- -1.79942021 0.517773009
- -1.30677990 0.830860762
- 1.70233874 0.291826660
- -3.05532536 0.801767829
- -4.06732625 0.092294501
- 6.34665476 0.270426235
- 9.46946411 0.196915311
- 14.50919907 0.480357167
- 8.93767237 0.778228613
- 1.90298854 0.903146151
- 18.50500507 0.598561307
- 4.45123027 0.555898218
- 11.37344114 0.616557707
--12.14693218 0.409187285
- 18.27198688 0.141619222
- -5.75939569 0.056989619
- -4.05515382 0.369281201
- 16.69882098 0.946885257
- 6.39050536 0.679704228
- 4.04213339 0.662792380
- 6.89608366 0.419877433
- 1.56496633 0.358227958
- 5.16679947 0.095144366
- -3.06280456 0.883265975
- 2.76279175 0.866571973
- 1.84969249 0.264869828
- 21.79840498 0.702650979
- 1.42450528 0.719308635
- 0.96797046 0.111937435
- 18.26840323 0.075621738
- 13.38288377 0.573399086
- 2.41101500 0.766238677
- 3.83866337 0.499888953
- -1.56577367 0.695244089
- -0.90342790 0.671654151
- 10.83775583 0.026041124
- -9.89767935 0.745297991
- 11.74840150 0.309144074
- 1.73069359 0.814063985
- -5.27966183 0.591005828
- 3.33030043 0.559401806
- 1.31427975 0.520950237
--10.04588558 0.507008362
- 10.41228345 0.425867272
- 1.71961097 0.595783108
--17.54904427 0.328788939
- -2.23545419 0.223377350
- -8.68774333 0.980964240
- -3.48048220 0.008877675
- -3.69635326 0.090236718
- 9.76114237 0.769375983
--10.25662038 0.508137553
- 0.11155446 0.468504431
- -8.06824580 0.414098962
- 3.10031660 0.327130207
- -3.33393146 0.756896774
- -3.96276749 0.530956360
- 14.53610268 0.846474699
- 1.70505918 0.754662464
- -1.93495001 0.656650411
- 5.01974522 0.745337633
- 13.41249973 0.489362476
- 11.49288744 0.335924476
- 12.59019763 0.155560469
--10.17947298 0.677318449
- 0.05556115 0.655090105
- 3.82092860 0.051838719
- 8.23041456 0.918272190
- -0.50314649 0.772015826
- 20.05162157 0.880265258
- 8.98816884 0.666646668
- -6.28312120 0.138534416
- 3.68589909 0.274559458
- 0.59699510 0.253180863
- -2.74783135 0.983525221
- 0.32515065 0.839969577
- -3.60606166 0.330646732
- -0.82037740 0.129591173
- 6.12444860 0.098536516
- 10.95671074 0.033546728
- -2.84911174 0.720288722
- 6.04597572 0.577061422
- -0.60147150 0.674096868
- -5.30458364 0.291468008
- 2.68044943 0.379853840
- 0.85986585 0.984214339
--12.77906359 0.882390290
- 7.21420144 0.550884826
- 2.31817022 0.231021556
- 11.60161950 0.888496654
- -0.19346228 0.242609713
- 5.07478120 0.759161318
- 14.54155003 0.040387654
- 3.81039636 0.874572741
- 2.23233049 0.448317248
- 0.19481869 0.201906051
- 2.81530451 0.132131690
- 12.39893259 0.674693704
- 0.47054642 0.632959494
- 2.16152913 0.734480632
- 0.33398836 0.315024718
- 7.35509037 0.304570986
- -2.92336559 0.539062343
- 5.79622573 0.392393310
- -2.37607425 0.403380474
- 0.04498550 0.756875541
- -1.63674414 0.613789514
- 11.80310547 0.832651469
- 6.30630243 0.850689403
- 1.48394652 0.096243229
- 4.03361865 0.799660045
- 3.54707273 0.408520520
- 2.00327040 0.702944912
- 17.30761707 0.380542812
- 5.72738968 0.105447516
--13.64604891 0.328506659
- 8.35976334 0.702173924
- -7.41197443 0.134396488
--15.95683040 0.618526462
- 8.76889573 0.950243069
- -1.13482624 0.113477080
- -0.60311407 0.090444247
- 4.95508365 0.612511543
- 5.36934491 0.979213258
- -0.03554882 0.807185690
--11.58131144 0.183341373
- 4.46809041 0.796330582
- 12.49741067 0.346860912
- 8.63824488 0.073684997
- 0.49990913 0.732519306
- 12.82688360 0.109400213
- 13.20375065 0.850369092
- -8.41110869 0.177717087
- 16.31959963 0.727704840
- 17.59203613 0.235311681
- 0.32148420 0.842195936
- 5.43148331 0.670904647
- 7.14649727 0.028190029
- 0.25410683 0.421535783
--12.41047826 0.086404379
--10.64180909 0.229659236
- -6.40185653 0.876365242
- 15.63063324 0.667672536
- 1.94280423 0.799266628
- -5.76507450 0.367344192
- 8.60895533 0.154109357
- 9.38306751 0.788742770
- 3.43573528 0.284535277
- 4.81848966 0.872283177
- 11.65839314 0.234109111
- -5.57884822 0.030363060
- -3.94238060 0.325320686
- 9.38133340 0.201141788
- -7.65003459 0.647734396
- 11.23091019 0.084927159
- -6.07705432 0.037273791
- 7.46380750 0.506897136
- 7.42034855 0.869351148
- -4.43031973 0.231191152
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- 1.70530391 0.621828438
--12.95649749 0.355726301
- 8.43735652 0.275383759
--15.56161079 0.413160084
- 5.28942694 0.069125495
- 5.96040877 0.438716686
- -2.59318107 0.571116303
- 6.95988992 0.650760909
- 14.00074797 0.623645969
- 1.66101456 0.558763985
- -2.57968349 0.648185379
- -5.47584253 0.716901151
- 6.37222581 0.060563130
- 2.83664864 0.842419730
- 1.48926558 0.620280308
- 0.33471689 0.170312461
- 5.21648412 0.317639631
- 0.51733642 0.843867329
- 9.86005834 0.306036746
- -5.81145791 0.975655452
- -5.43219061 0.303385368
- 5.87157118 0.677369776
- 2.08889926 0.310200439
- -2.53433085 0.194730908
- 7.01359575 0.674259533
- -2.00936260 0.682056466
- -2.98240739 0.787899917
- -7.43289210 0.357483044
--12.58905988 0.981387385
- 5.78095517 0.533526274
- -1.23065889 0.687266774
- -6.82309960 0.293249774
- 8.47000829 0.842056399
- -5.81624772 0.303700280
--14.83571031 0.311387926
- 4.66808472 0.091222946
- -2.90144463 0.438301785
- 10.62458662 0.828335698
- 7.88002491 0.990156110
- 10.27680283 0.251087079
- -9.42498970 0.292462244
- 6.73027640 0.213065205
- 1.28169895 0.353152789
--14.29203733 0.264563048
- 20.35772711 0.265208837
- 3.55095071 0.242905653
--17.97067670 0.373951756
- 10.53141139 0.247520698
- 0.05293205 0.579940423
- 12.79674707 0.288031751
- -5.44235185 0.075899079
- 14.29464811 0.960707538
- -1.36753291 0.124265178
- -4.25946974 0.521720352
--12.46519252 0.385503339
- -6.65343143 0.540942219
- 5.55949184 0.143194404
- -1.20480594 0.515905644
- -4.13839908 0.164461445
- -2.21345425 0.812969725
- 3.94223380 0.229238952
--10.78661097 0.395049514
- 3.06997341 0.791234255
- 24.82205477 0.110859039
- 6.28791249 0.867125744
- -2.80296119 0.703583849
- 13.24274039 0.425951975
- -0.19577471 0.361568727
- -2.34894781 0.954814545
- 19.76339577 0.635462177
- -1.87591480 0.149121567
- -7.70962391 0.711708342
- -2.46291902 0.390902746
-end data
-regression /variables=v0 v1 /statistics defaults /dependent=v0 /method=enter.
-])
-
-AT_CHECK([pspp -O format=csv regression.sps], [0], [dnl
-Table: Reading free-form data from INLINE.
-Variable,Format
-v0,F8.0
-v1,F8.0
-
-Table: Model Summary (v0)
-R,R Square,Adjusted R Square,Std. Error of the Estimate
-.05,.00,.00,8.11
-
-Table: ANOVA (v0)
-,Sum of Squares,df,Mean Square,F,Sig.
-Regression,235.23,1,235.23,3.58,.059
-Residual,98438.40,1498,65.71,,
-Total,98673.63,1499,,,
-
-Table: Coefficients (v0)
-,Unstandardized Coefficients,,Standardized Coefficients,t,Sig.
-,B,Std. Error,Beta,,
-(Constant),1.24,.42,.00,2.95,.003
-v1,1.37,.72,.05,1.89,.059
-])
-
-AT_CLEANUP
-
-AT_SETUP([LINEAR REGRESSION no crash on all missing])
-AT_DATA([regcrash.sps], [dnl
-data list list /x * y.
-begin data.
- . .
- . .
- . .
- . .
- . .
- . .
- . .
- . .
- . .
- . .
-end data.
-
-
-regression /variables=x y /dependent=y.
-])
-
-AT_CHECK([pspp -o pspp.csv regcrash.sps], [1], [ignore], [ignore])
-
-AT_CLEANUP
-
-
-
-AT_SETUP([LINEAR REGRESSION missing dependent variable])
-
-dnl Test for a bug where missing values in the dependent variable were not being
-dnl ignored like they should have been.
-AT_DATA([reg-mdv-ref.sps], [dnl
-data list notable list / v0 to v2.
-begin data
- 0.65377128 7.735648 -23.97588
--0.13087553 6.142625 -19.63854
- 0.34880368 7.651430 -25.26557
- 0.69249021 6.125125 -16.57090
--0.07368178 8.245789 -25.80001
--0.34404919 6.031540 -17.56743
- 0.75981559 9.832291 -28.35977
--0.46958313 5.343832 -16.79548
--0.06108490 8.838262 -29.25689
- 0.56154863 6.200189 -18.58219
-end data
-regression /variables=v0 v1
- /statistics defaults
- /dependent=v2
- /method=enter.
-])
-
-AT_CHECK([pspp -o pspp-ref.csv reg-mdv-ref.sps])
-
-AT_DATA([reg-mdv.sps], [dnl
-data list notable list / v0 to v2.
-begin data
- 0.65377128 7.735648 -23.97588
--0.13087553 6.142625 -19.63854
- 0.34880368 7.651430 -25.26557
- 0.69249021 6.125125 -16.57090
--0.07368178 8.245789 -25.80001
--0.34404919 6.031540 -17.56743
- 0.75981559 9.832291 -28.35977
--0.46958313 5.343832 -16.79548
--0.06108490 8.838262 -29.25689
- 0.56154863 6.200189 -18.58219
- 0.5 8 9
-end data
-
-missing values v2 (9).
-
-regression /variables=v0 v1
- /statistics defaults
- /dependent=v2
- /method=enter.
-])
-
-AT_CHECK([pspp -o pspp.csv reg-mdv.sps])
-
-AT_CHECK([diff pspp.csv pspp-ref.csv])
-
-
-AT_CLEANUP
-
-AT_SETUP([LINEAR REGRESSION with invalid syntax (and empty dataset)])
-
-AT_DATA([ss.sps], [dnl
-data list notable list / v0 to v2.
-begin data
-end data.
-
-regression /variables=v0 v1
- /statistics r coeff anova
- /dependent=v2
- /method=enter v2.
-])
-
-AT_CHECK([pspp ss.sps], [1], [ignore])
-
-AT_CLEANUP
-
-
-dnl The following example comes from
-dnl http://www.ats.ucla.edu/stat/spss/output/reg_spss%28long%29.htm
-AT_SETUP([LINEAR REGRESSION coefficient confidence interval])
-
-AT_DATA([conf.sps], [dnl
-set format = F22.3.
-
-data list notable list /math female socst read science *
-begin data.
- 41.00 .00 57.00 57.00 47.00
- 53.00 1.00 61.00 68.00 63.00
- 54.00 .00 31.00 44.00 58.00
- 47.00 .00 56.00 63.00 53.00
- 57.00 .00 61.00 47.00 53.00
- 51.00 .00 61.00 44.00 63.00
- 42.00 .00 61.00 50.00 53.00
- 45.00 .00 36.00 34.00 39.00
- 54.00 .00 51.00 63.00 58.00
- 52.00 .00 51.00 57.00 50.00
- 51.00 .00 61.00 60.00 53.00
- 51.00 .00 61.00 57.00 63.00
- 71.00 .00 71.00 73.00 61.00
- 57.00 .00 46.00 54.00 55.00
- 50.00 .00 56.00 45.00 31.00
- 43.00 .00 56.00 42.00 50.00
- 51.00 .00 56.00 47.00 50.00
- 60.00 .00 56.00 57.00 58.00
- 62.00 .00 61.00 68.00 55.00
- 57.00 .00 46.00 55.00 53.00
- 35.00 .00 41.00 63.00 66.00
- 75.00 .00 66.00 63.00 72.00
- 45.00 .00 56.00 50.00 55.00
- 57.00 .00 61.00 60.00 61.00
- 45.00 .00 46.00 37.00 39.00
- 46.00 .00 31.00 34.00 39.00
- 66.00 .00 66.00 65.00 61.00
- 57.00 .00 46.00 47.00 58.00
- 49.00 .00 46.00 44.00 39.00
- 49.00 .00 41.00 52.00 55.00
- 57.00 .00 51.00 42.00 47.00
- 64.00 .00 61.00 76.00 64.00
- 63.00 .00 71.00 65.00 66.00
- 57.00 .00 31.00 42.00 72.00
- 50.00 .00 61.00 52.00 61.00
- 58.00 .00 66.00 60.00 61.00
- 75.00 .00 66.00 68.00 66.00
- 68.00 .00 66.00 65.00 66.00
- 44.00 .00 36.00 47.00 36.00
- 40.00 .00 51.00 39.00 39.00
- 41.00 .00 51.00 47.00 42.00
- 62.00 .00 51.00 55.00 58.00
- 57.00 .00 51.00 52.00 55.00
- 43.00 .00 41.00 42.00 50.00
- 48.00 .00 66.00 65.00 63.00
- 63.00 .00 46.00 55.00 69.00
- 39.00 .00 47.00 50.00 49.00
- 70.00 .00 51.00 65.00 63.00
- 63.00 .00 46.00 47.00 53.00
- 59.00 .00 51.00 57.00 47.00
- 61.00 .00 56.00 53.00 57.00
- 38.00 .00 41.00 39.00 47.00
- 61.00 .00 46.00 44.00 50.00
- 49.00 .00 71.00 63.00 55.00
- 73.00 .00 66.00 73.00 69.00
- 44.00 .00 42.00 39.00 26.00
- 42.00 .00 32.00 37.00 33.00
- 39.00 .00 46.00 42.00 56.00
- 55.00 .00 41.00 63.00 58.00
- 52.00 .00 51.00 48.00 44.00
- 45.00 .00 61.00 50.00 58.00
- 61.00 .00 66.00 47.00 69.00
- 39.00 .00 46.00 44.00 34.00
- 41.00 .00 36.00 34.00 36.00
- 50.00 .00 61.00 50.00 36.00
- 40.00 .00 26.00 44.00 50.00
- 60.00 .00 66.00 60.00 55.00
- 47.00 .00 26.00 47.00 42.00
- 59.00 .00 44.00 63.00 65.00
- 49.00 .00 36.00 50.00 44.00
- 46.00 .00 51.00 44.00 39.00
- 58.00 .00 61.00 60.00 58.00
- 71.00 .00 66.00 73.00 63.00
- 58.00 .00 66.00 68.00 74.00
- 46.00 .00 51.00 55.00 58.00
- 43.00 .00 31.00 47.00 45.00
- 54.00 .00 61.00 55.00 49.00
- 56.00 .00 66.00 68.00 63.00
- 46.00 .00 46.00 31.00 39.00
- 54.00 .00 56.00 47.00 42.00
- 57.00 .00 56.00 63.00 55.00
- 54.00 .00 36.00 36.00 61.00
- 71.00 .00 56.00 68.00 66.00
- 48.00 .00 56.00 63.00 63.00
- 40.00 .00 41.00 55.00 44.00
- 64.00 .00 66.00 55.00 63.00
- 51.00 .00 56.00 52.00 53.00
- 39.00 .00 56.00 34.00 42.00
- 40.00 .00 31.00 50.00 34.00
- 61.00 .00 56.00 55.00 61.00
- 66.00 .00 46.00 52.00 47.00
- 49.00 .00 46.00 63.00 66.00
- 65.00 1.00 61.00 68.00 69.00
- 52.00 1.00 48.00 39.00 44.00
- 46.00 1.00 51.00 44.00 47.00
- 61.00 1.00 51.00 50.00 63.00
- 72.00 1.00 56.00 71.00 66.00
- 71.00 1.00 71.00 63.00 69.00
- 40.00 1.00 41.00 34.00 39.00
- 69.00 1.00 61.00 63.00 61.00
- 64.00 1.00 66.00 68.00 69.00
- 56.00 1.00 61.00 47.00 66.00
- 49.00 1.00 41.00 47.00 33.00
- 54.00 1.00 51.00 63.00 50.00
- 53.00 1.00 51.00 52.00 61.00
- 66.00 1.00 56.00 55.00 42.00
- 67.00 1.00 56.00 60.00 50.00
- 40.00 1.00 33.00 35.00 51.00
- 46.00 1.00 56.00 47.00 50.00
- 69.00 1.00 71.00 71.00 58.00
- 40.00 1.00 56.00 57.00 61.00
- 41.00 1.00 51.00 44.00 39.00
- 57.00 1.00 66.00 65.00 46.00
- 58.00 1.00 56.00 68.00 59.00
- 57.00 1.00 66.00 73.00 55.00
- 37.00 1.00 41.00 36.00 42.00
- 55.00 1.00 46.00 43.00 55.00
- 62.00 1.00 66.00 73.00 58.00
- 64.00 1.00 56.00 52.00 58.00
- 40.00 1.00 51.00 41.00 39.00
- 50.00 1.00 51.00 60.00 50.00
- 46.00 1.00 56.00 50.00 50.00
- 53.00 1.00 56.00 50.00 39.00
- 52.00 1.00 46.00 47.00 48.00
- 45.00 1.00 46.00 47.00 34.00
- 56.00 1.00 61.00 55.00 58.00
- 45.00 1.00 56.00 50.00 44.00
- 54.00 1.00 41.00 39.00 50.00
- 56.00 1.00 46.00 50.00 47.00
- 41.00 1.00 26.00 34.00 29.00
- 54.00 1.00 56.00 57.00 50.00
- 72.00 1.00 56.00 57.00 54.00
- 56.00 1.00 51.00 68.00 50.00
- 47.00 1.00 46.00 42.00 47.00
- 49.00 1.00 66.00 61.00 44.00
- 60.00 1.00 66.00 76.00 67.00
- 54.00 1.00 46.00 47.00 58.00
- 55.00 1.00 56.00 46.00 44.00
- 33.00 1.00 41.00 39.00 42.00
- 49.00 1.00 61.00 52.00 44.00
- 43.00 1.00 51.00 28.00 44.00
- 50.00 1.00 52.00 42.00 50.00
- 52.00 1.00 51.00 47.00 39.00
- 48.00 1.00 41.00 47.00 44.00
- 58.00 1.00 66.00 52.00 53.00
- 43.00 1.00 61.00 47.00 48.00
- 41.00 1.00 31.00 50.00 55.00
- 43.00 1.00 51.00 44.00 44.00
- 46.00 1.00 41.00 47.00 40.00
- 44.00 1.00 41.00 45.00 34.00
- 43.00 1.00 46.00 47.00 42.00
- 61.00 1.00 56.00 65.00 58.00
- 40.00 1.00 51.00 43.00 50.00
- 49.00 1.00 61.00 47.00 53.00
- 56.00 1.00 66.00 57.00 58.00
- 61.00 1.00 71.00 68.00 55.00
- 50.00 1.00 61.00 52.00 54.00
- 51.00 1.00 61.00 42.00 47.00
- 42.00 1.00 41.00 42.00 42.00
- 67.00 1.00 66.00 66.00 61.00
- 53.00 1.00 61.00 47.00 53.00
- 50.00 1.00 58.00 57.00 51.00
- 51.00 1.00 31.00 47.00 63.00
- 72.00 1.00 61.00 57.00 61.00
- 48.00 1.00 61.00 52.00 55.00
- 40.00 1.00 31.00 44.00 40.00
- 53.00 1.00 61.00 50.00 61.00
- 39.00 1.00 36.00 39.00 47.00
- 63.00 1.00 41.00 57.00 55.00
- 51.00 1.00 37.00 57.00 53.00
- 45.00 1.00 43.00 42.00 50.00
- 39.00 1.00 61.00 47.00 47.00
- 42.00 1.00 39.00 42.00 31.00
- 62.00 1.00 51.00 60.00 61.00
- 44.00 1.00 51.00 44.00 35.00
- 65.00 1.00 66.00 63.00 54.00
- 63.00 1.00 71.00 65.00 55.00
- 54.00 1.00 41.00 39.00 53.00
- 45.00 1.00 36.00 50.00 58.00
- 60.00 1.00 51.00 52.00 56.00
- 49.00 1.00 51.00 60.00 50.00
- 48.00 1.00 51.00 44.00 39.00
- 57.00 1.00 61.00 52.00 63.00
- 55.00 1.00 61.00 55.00 50.00
- 66.00 1.00 56.00 50.00 66.00
- 64.00 1.00 71.00 65.00 58.00
- 55.00 1.00 51.00 52.00 53.00
- 42.00 1.00 36.00 47.00 42.00
- 56.00 1.00 61.00 63.00 55.00
- 53.00 1.00 66.00 50.00 53.00
- 41.00 1.00 41.00 42.00 42.00
- 42.00 1.00 41.00 36.00 50.00
- 53.00 1.00 56.00 50.00 55.00
- 42.00 1.00 51.00 41.00 34.00
- 60.00 1.00 56.00 47.00 50.00
- 52.00 1.00 56.00 55.00 42.00
- 38.00 1.00 46.00 42.00 36.00
- 57.00 1.00 52.00 57.00 55.00
- 58.00 1.00 61.00 55.00 58.00
- 65.00 1.00 61.00 63.00 53.00
-end data.
-
-regression
- /variables = math female socst read
- /statistics = coeff r anova ci (95)
- /dependent = science
- /method = enter
-])
-
-AT_CHECK([pspp -O format=csv conf.sps], [0], [dnl
-Table: Model Summary (science)
-R,R Square,Adjusted R Square,Std. Error of the Estimate
-.699,.489,.479,7.148
-
-Table: ANOVA (science)
-,Sum of Squares,df,Mean Square,F,Sig.
-Regression,9543.721,4,2385.930,46.695,.000
-Residual,9963.779,195,51.096,,
-Total,19507.500,199,,,
-
-Table: Coefficients (science)
-,Unstandardized Coefficients,,Standardized Coefficients,t,Sig.,95% Confidence Interval for B,
-,B,Std. Error,Beta,,,Lower Bound,Upper Bound
-(Constant),12.325,3.194,.000,3.859,.000,6.027,18.624
-math,.389,.074,.368,5.252,.000,.243,.535
-female,-2.010,1.023,-.101,-1.965,.051,-4.027,.007
-socst,.050,.062,.054,.801,.424,-.073,.173
-read,.335,.073,.347,4.607,.000,.192,.479
-])
-
-
-AT_CLEANUP
-
-
-dnl Checks for regression against bug #44877.
-AT_SETUP([LINEAR REGRESSION crash with long string variables])
-AT_DATA([regression.sps], [dnl
-SET DECIMAL=DOT.
-
-DATA LIST notable LIST /text (A24) Y * X1 *
-BEGIN DATA.
-V00276601 0.00 90.00
-V00292909 10.00 30.00
-V00291204 20.00 20.00
-V00300070 0.00 90.00
-END DATA.
-
-REGRESSION
-/VARIABLES= Y
-/DEPENDENT= X1
-/METHOD=ENTER
-/STATISTICS=COEFF R ANOVA
-/SAVE= RESID.
-
-LIST.
-])
-AT_CHECK([pspp -o pspp.csv regression.sps])
-AT_CHECK([cat pspp.csv], [0], [dnl
-Table: Model Summary (X1)
-R,R Square,Adjusted R Square,Std. Error of the Estimate
-.95,.89,.84,15.08
-
-Table: ANOVA (X1)
-,Sum of Squares,df,Mean Square,F,Sig.
-Regression,3820.45,1,3820.45,16.81,.055
-Residual,454.55,2,227.27,,
-Total,4275.00,3,,,
-
-Table: Coefficients (X1)
-,Unstandardized Coefficients,,Standardized Coefficients,t,Sig.
-,B,Std. Error,Beta,,
-(Constant),85.45,10.16,.00,8.41,.004
-Y,-3.73,.91,-.95,-4.10,.055
-
-Table: Data List
-text,Y,X1,RES1
-V00276601,.00,90.00,4.55
-V00292909,10.00,30.00,-18.18
-V00291204,20.00,20.00,9.09
-V00300070,.00,90.00,4.55
-])
-AT_CLEANUP
-
-
-dnl Test for a crash which happened on bad input syntax
-AT_SETUP([LINEAR REGRESSION -- Empty Parentheses])
-
-AT_DATA([empty-parens.sps], [dnl
-set format = F22.3.
-
-data list notable list /math female socst read science *
-begin data.
- 58.00 1.00 61.00 55.00 58.00
- 65.00 1.00 61.00 63.00 53.00
-end data.
-
-regression
- /variables = math female socst read
- /statistics = coeff r anova ci ()
- /dependent = science
- /method = enter
-])
-
-AT_CHECK([pspp -o pspp.csv empty-parens.sps], [1], [ignore])
-
-AT_CLEANUP
-
-
-
-
-AT_SETUP([LINEAR REGRESSION varibles on ENTER subcommand])
-AT_DATA([regression.sps], [dnl
-SET FORMAT=F10.3.
-
-DATA LIST notable LIST /number * value *.
-BEGIN DATA
- 16 7.25
- 0 .00
- 1 .10
- 9 27.9
- 0 .00
- 7 3.65
- 14 16.8
- 24 9.15
- 0 .00
- 24 19.0
- 7 4.05
- 12 7.90
- 6 .75
- 11 1.40
- 0 .00
- 3 2.30
- 12 7.60
- 11 6.80
- 16 8.65
-END DATA.
-
-REGRESSION
- /STATISTICS COEFF R ANOVA
- /DEPENDENT value
- /METHOD=ENTER number.
-])
-
-
-AT_CHECK([pspp -O format=csv regression.sps], [0], [dnl
-Table: Model Summary (value)
-R,R Square,Adjusted R Square,Std. Error of the Estimate
-.612,.374,.338,6.176
-
-Table: ANOVA (value)
-,Sum of Squares,df,Mean Square,F,Sig.
-Regression,388.065,1,388.065,10.173,.005
-Residual,648.498,17,38.147,,
-Total,1036.563,18,,,
-
-Table: Coefficients (value)
-,Unstandardized Coefficients,,Standardized Coefficients,t,Sig.
-,B,Std. Error,Beta,,
-(Constant),.927,2.247,.000,.413,.685
-number,.611,.192,.612,3.189,.005
-])
-
-AT_CLEANUP
-
-
-
-AT_SETUP([LINEAR REGRESSION /ORIGIN])
-AT_DATA([regression-origin.sps], [dnl
-SET FORMAT=F10.3.
-
-DATA LIST notable LIST /number * value *.
-BEGIN DATA
- 16 7.25
- 0 .00
- 1 .10
- 9 27.9
- 0 .00
- 7 3.65
- 14 16.8
- 24 9.15
- 0 .00
- 24 19.0
- 7 4.05
- 12 7.90
- 6 .75
- 11 1.40
- 0 .00
- 3 2.30
- 12 7.60
- 11 6.80
- 16 8.65
-END DATA.
-
-REGRESSION
- /STATISTICS COEFF R ANOVA
- /DEPENDENT value
- /ORIGIN
- /METHOD=ENTER number.
-])
-
-
-AT_CHECK([pspp -O format=csv regression-origin.sps], [0], [dnl
-Table: Model Summary (value)
-R,R Square,Adjusted R Square,Std. Error of the Estimate
-.802,.643,.622,6.032
-
-Table: ANOVA (value)
-,Sum of Squares,df,Mean Square,F,Sig.
-Regression,1181.726,1,1181.726,32.475,.000
-Residual,654.989,18,36.388,,
-Total,1836.715,19,,,
-
-Table: Coefficients (value)
-,Unstandardized Coefficients,,Standardized Coefficients,t,Sig.
-,B,Std. Error,Beta,,
-number,.672,.118,.802,5.699,.000
-])
-
-AT_CLEANUP
-
-dnl This is an example from doc/tutorial.texi
-dnl So if the results of this have to be changed in any way,
-dnl make sure to update that file.
-AT_SETUP([REGRESSION tutorial example])
-cp $top_srcdir/examples/repairs.sav .
-AT_DATA([regression.sps], [dnl
-GET FILE='repairs.sav'.
-REGRESSION /VARIABLES=mtbf duty_cycle /DEPENDENT=mttr.
-REGRESSION /VARIABLES=mtbf /DEPENDENT=mttr.
-])
-
-AT_CHECK([pspp -O format=csv regression.sps], [0], [dnl
-Table: Model Summary (Mean time to repair (hours) )
-R,R Square,Adjusted R Square,Std. Error of the Estimate
-.94,.89,.88,6.54
-
-Table: ANOVA (Mean time to repair (hours) )
-,Sum of Squares,df,Mean Square,F,Sig.
-Regression,9576.26,2,4788.13,111.94,.000
-Residual,1154.94,27,42.78,,
-Total,10731.20,29,,,
-
-Table: Coefficients (Mean time to repair (hours) )
-,Unstandardized Coefficients,,Standardized Coefficients,t,Sig.
-,B,Std. Error,Beta,,
-(Constant),10.59,3.11,.00,3.40,.002
-Mean time between failures (months) ,3.02,.20,.95,14.88,.000
-Ratio of working to non-working time,-1.12,3.69,-.02,-.30,.763
-
-Table: Model Summary (Mean time to repair (hours) )
-R,R Square,Adjusted R Square,Std. Error of the Estimate
-.94,.89,.89,6.43
-
-Table: ANOVA (Mean time to repair (hours) )
-,Sum of Squares,df,Mean Square,F,Sig.
-Regression,9572.30,1,9572.30,231.28,.000
-Residual,1158.90,28,41.39,,
-Total,10731.20,29,,,
-
-Table: Coefficients (Mean time to repair (hours) )
-,Unstandardized Coefficients,,Standardized Coefficients,t,Sig.
-,B,Std. Error,Beta,,
-(Constant),9.90,2.10,.00,4.71,.000
-Mean time between failures (months) ,3.01,.20,.94,15.21,.000
-])
-
-AT_CLEANUP
-
-
-AT_SETUP([LINEAR REGRESSION vif])
-AT_DATA([regression-vif.sps], [dnl
-SET FORMAT=F10.3.
-
-data list notable list /competence_x1 motivation_x2 performance_y.
-begin data
-32 34 36
-35 37 39
-38 45 49
-31 41 41
-36 40 38
-32 38 36
-33 39 37
-31 40 41
-30 37 40
-35 37 43
-31 34 36
-34 32 35
-31 42 34
-25 36 40
-35 42 40
-36 41 44
-30 38 32
-34 41 41
-34 41 44
-22 27 26
-27 26 33
-30 30 35
-30 35 37
-37 39 44
-29 35 36
-31 35 29
-31 45 41
-29 30 32
-29 35 36
-31 37 37
-36 45 42
-32 44 39
-27 26 31
-33 39 35
-20 25 28
-30 36 39
-27 37 39
-25 39 36
-32 38 38
-32 38 35
-end data.
-
-regression /variables=competence_x1 motivation_x2
- /statistics=defaults tol
- /dependent=performance_y
- .
-])
-
-
-AT_CHECK([pspp -O format=csv regression-vif.sps], [0], [dnl
-Table: Model Summary (performance_y)
-R,R Square,Adjusted R Square,Std. Error of the Estimate
-.785,.616,.595,2.980
-
-Table: ANOVA (performance_y)
-,Sum of Squares,df,Mean Square,F,Sig.
-Regression,526.494,2,263.247,29.641,.000
-Residual,328.606,37,8.881,,
-Total,855.100,39,,,
-
-Table: Coefficients (performance_y)
-,Unstandardized Coefficients,,Standardized Coefficients,t,Sig.,Collinearity Statistics,
-,B,Std. Error,Beta,,,Tolerance,VIF
-(Constant),7.220,4.020,.000,1.796,.080,,
-competence_x1,.432,.166,.358,2.609,.013,.552,1.812
-motivation_x2,.453,.125,.499,3.636,.001,.552,1.812
-])
-
-AT_CLEANUP
-
-AT_SETUP([REGRESSION syntax errors])
-AT_DATA([regression.sps], [dnl
-DATA LIST LIST NOTABLE /x y z.
-REGRESSION VARIABLES=**.
-REGRESSION METHOD=ENTER x/VARIABLES.
-REGRESSION DEPENDENT=x/VARIABLES.
-REGRESSION DEPENDENT=**.
-REGRESSION METHOD=**.
-REGRESSION METHOD=ENTER **.
-REGRESSION STATISTICS=**.
-REGRESSION STATISTICS=CI(**).
-REGRESSION STATISTICS=CI(1 **).
-REGRESSION SAVE=**.
-REGRESSION **.
-])
-AT_CHECK([pspp -O format=csv regression.sps], [1], [dnl
-"regression.sps:2.22-2.23: error: REGRESSION: Syntax error expecting variable name.
- 2 | REGRESSION VARIABLES=**.
- | ^~"
-
-"regression.sps:3.27-3.35: error: REGRESSION: VARIABLES may not appear after METHOD.
- 3 | REGRESSION METHOD=ENTER x/VARIABLES.
- | ^~~~~~~~~"
-
-"regression.sps:4.24-4.32: error: REGRESSION: VARIABLES may not appear after DEPENDENT.
- 4 | REGRESSION DEPENDENT=x/VARIABLES.
- | ^~~~~~~~~"
-
-"regression.sps:5.22-5.23: error: REGRESSION: Syntax error expecting variable name.
- 5 | REGRESSION DEPENDENT=**.
- | ^~"
-
-"regression.sps:6.19-6.20: error: REGRESSION: Syntax error expecting ENTER.
- 6 | REGRESSION METHOD=**.
- | ^~"
-
-"regression.sps:7.25-7.26: error: REGRESSION: Syntax error expecting variable name.
- 7 | REGRESSION METHOD=ENTER **.
- | ^~"
-
-"regression.sps:8.23-8.24: error: REGRESSION: Syntax error expecting ALL, DEFAULTS, R, COEFF, ANOVA, BCOV, TOL, or CI.
- 8 | REGRESSION STATISTICS=**.
- | ^~"
-
-"regression.sps:9.26-9.27: error: REGRESSION: Syntax error expecting number.
- 9 | REGRESSION STATISTICS=CI(**).
- | ^~"
-
-"regression.sps:10.28-10.29: error: REGRESSION: Syntax error expecting `@:}@'.
- 10 | REGRESSION STATISTICS=CI(1 **).
- | ^~"
-
-"regression.sps:11.17-11.18: error: REGRESSION: Syntax error expecting PRED or RESID.
- 11 | REGRESSION SAVE=**.
- | ^~"
-
-"regression.sps:12.12-12.13: error: REGRESSION: Syntax error expecting VARIABLES, DEPENDENT, ORIGIN, NOORIGIN, METHOD, STATISTICS, or SAVE.
- 12 | REGRESSION **.
- | ^~"
-])
-AT_CLEANUP
\ No newline at end of file
projects / pspp / blobdiff