predict.selection: Predict method for fitted sample selection models
In sampleSelection: Sample Selection Models
Description
Usage
Arguments
Value
Author(s)
See Also
Examples
View source: R/predict.selection.R
Description
Calculate predicted values for sample selection models
fitted with function selection.
Usage
1
2
3
4
5
Arguments
object
a fitted object of class selection.
newdata
optionally, a data frame in which to look for variables
with which to predict.
If omitted, the fitted linear predictors or the fitted response values
are returned.
part
character string indicating for which equation
the predicted variables should be calculated:
"selection" for the predicted values of the selection equation and
"outcome" for the predicted values of the outcome equation;
this argument is automatically chosen depending on the value
of argument type.
type
if argument type is "link"
and argument part is "selection",
the linear predictors of the selection equation are returned;
if argument type is "response"
and argument part is "selection",
the predicted probabilities of the selection equation are returned;
if argument type is "unconditional"
and argument part is "outcome",
the unconditional expectations are returned,
i.e. E[y|X] = X %*% beta;
if argument type is "conditional"
and argument part is "outcome",
the conditional expectations are returned,
i.e. E[y|X,Z,w=1] = X %*% beta
+ rho * sigma * dnorm( Z %*% gamma ) / pnorm( Z %*% gamma ).
...
further arguments (currently ignored).
Value
In most cases, a numeric vector of the predicted values is returned.
However, there are three exceptions:
(i) when predicting the unconditional expectations of a Tobit-5 model,
a matrix with two columns is returned,
where the two columns correspond to the two outcome equations
(E[yo1] and E[yo2]);
(ii) when predicting the conditional expectations of a Tobit-2 model,
a matrix with two columns is returned,
where the first column returns the expectations
conditional on the observation being not selected (E[yo|ys=0]),
while the second column returns the expectations
conditional on the observation being selected (E[yo|ys=1]);
(iii) when predicting the conditional expectations of a Tobit-5 model,
a matrix with four columns is returned,
where the first two columns return the conditional expectations
of the first outcome equation (E[yo1|ys=0] and E[yo1|ys=1])
and the last two columns return the conditional expectations
of the second outcome equation (E[yo2|ys=0] and E[yo2|ys=1]).
Author(s)
Arne Henningsen and ‘fg nu’
(the code is partly based on the code posted by ‘fg nu’ at
https://stackoverflow.com/questions/14005788/predict-function-for-heckman-model)
See Also
selection, predict,
predict.probit, residuals.selection,
and selection-methods.
Examples
1
2
3
4
5
6
7
8
9
10
11
12
13
## Greene( 2003 ): example 22.8, page 786
data( Mroz87 )
Mroz87$kids <- ( Mroz87$kids5 + Mroz87$kids618 > 0 )
# ML estimation
m <- selection( lfp ~ age + I( age^2 ) + faminc + kids + educ,
wage ~ exper + I( exper^2 ) + educ + city, Mroz87 )
predict( m )
predict( m, type = "conditional" )
predict( m, type = "link" )
predict( m, type = "response" )
predict( m, newdata = Mroz87[ 3:9, ] )
Example output
Loading required package: maxLik
Loading required package: miscTools
Please cite the 'maxLik' package as:
Henningsen, Arne and Toomet, Ott (2011). maxLik: A package for maximum likelihood estimation in R. Computational Statistics 26(3), 443-458. DOI 10.1007/s00180-010-0217-1.
If you have questions, suggestions, or comments regarding the 'maxLik' package, please use a forum or 'tracker' at maxLik's R-Forge site:
https://r-forge.r-project.org/projects/maxlik/
1 2 3 4 5 6 7 8
3.890836 4.104311 3.915693 3.684508 5.071565 4.774115 5.643041 4.369198
9 10 11 12 13 14 15 16
4.130052 4.060469 3.915693 3.433831 3.521037 4.337365 3.217026 3.752963
17 18 19 20 21 22 23 24
4.483388 4.131037 4.553594 3.763439 5.485802 3.815021 4.892549 3.915693
25 26 27 28 29 30 31 32
4.077377 6.792023 4.731673 4.209968 5.996051 3.711026 4.295993 6.089570
33 34 35 36 37 38 39 40
4.397346 4.337365 6.472316 3.064032 4.411311 3.305912 5.044062 6.546575
41 42 43 44 45 46 47 48
3.548801 4.337365 5.959057 3.789334 3.684508 3.630848 6.063883 4.083871
49 50 51 52 53 54 55 56
3.940341 3.684508 4.287029 4.752998 3.915693 2.583291 3.434486 6.037988
57 58 59 60 61 62 63 64
5.770518 6.520888 5.729737 4.131037 4.927051 4.235863 2.433530 4.362222
65 66 67 68 69 70 71 72
4.287029 2.012480 6.175862 4.261550 4.209968 4.130052 4.287029 4.312301
73 74 75 76 77 78 79 80
3.317384 3.347540 4.312301 4.459570 3.576358 6.861607 5.580983 4.131037
81 82 83 84 85 86 87 88
1.788369 5.177621 4.235863 5.045047 2.870855 6.973425 5.293226 3.088555
89 90 91 92 93 94 95 96
5.554880 3.865772 4.386870 4.261550 4.362222 4.131037 3.865772 4.083871
97 98 99 100 101 102 103 104
4.576581 4.479892 3.684508 4.033363 4.022887 3.890836 4.209968 6.089570
105 106 107 108 109 110 111 112
3.763439 4.588042 3.556036 4.175403 4.459570 4.050236 6.442580 5.580462
113 114 115 116 117 118 119 120
6.140322 6.494993 4.362222 4.026382 4.688400 4.209968 6.280356 3.269855
121 122 123 124 125 126 127 128
4.916575 3.650060 3.603707 5.693793 6.468891 3.964782 5.905398 3.915693
129 130 131 132 133 134 135 136
5.643041 1.883005 3.521037 3.521037 4.235863 4.640870 3.565882 4.077377
137 138 139 140 141 142 143 144
4.131037 5.349555 4.050236 4.530400 4.774115 6.951477 5.467605 4.197766
145 146 147 148 149 150 151 152
2.890535 4.131037 4.261550 4.337365 5.325321 6.239332 6.175862 5.632565
153 154 155 156 157 158 159 160
4.157555 6.011886 6.416062 6.468891 3.630848 6.427381 4.587057 4.261550
161 162 163 164 165 166 167 168
4.002565 6.037988 5.373580 5.718857 4.530400 2.760021 6.838620 5.276232
169 170 171 172 173 174 175 176
4.131037 3.815021 3.119353 4.530400 4.235863 3.423355 4.287029 1.010932
177 178 179 180 181 182 183 184
6.150798 3.532010 3.737336 4.261550 5.123978 3.752963 4.337365 5.123978
185 186 187 188 189 190 191 192
4.022887 2.926490 6.190242 4.718555 3.711026 4.209968 4.013041 3.358016
193 194 195 196 197 198 199 200
4.183865 2.941286 4.534382 4.157555 4.013041 4.337365 4.794370 5.878256
201 202 203 204 205 206 207 208
4.209968 5.985575 6.442580 3.890836 4.241871 2.642025 4.337365 3.940341
209 210 211 212 213 214 215 216
4.692868 3.840500 4.576581 3.684508 4.209968 2.976826 4.175403 5.539046
217 218 219 220 221 222 223 224
4.077377 3.458688 4.553594 2.634791 4.688400 4.209968 3.684508 3.815021
225 226 227 228 229 230 231 232
6.239332 6.416062 4.157555 6.307912 4.576581 3.630848 3.815021 2.324811
233 234 235 236 237 238 239 240
3.815021 4.479892 4.013041 4.157555 2.194867 4.483388 6.520888 6.744595
241 242 243 244 245 246 247 248
4.411311 4.744035 4.261550 4.131037 4.235863 3.630848 2.651872 3.398291
249 250 251 252 253 254 255 256
4.060469 6.037988 4.534382 1.748338 6.287590 4.534382 4.209968 3.880360
257 258 259 260 261 262 263 264
4.588042 4.576581 3.548801 3.398291 4.050236 6.520888 5.757886 6.037988
265 266 267 268 269 270 271 272
3.099031 3.620372 4.235863 4.104311 5.071565 5.431727 5.344068 2.112321
273 274 275 276 277 278 279 280
1.580747 3.548801 3.711026 5.276232 4.235863 3.576358 4.459570 5.513371
281 282 283 284 285 286 287 288
6.427381 4.157555 4.362222 4.261550 5.056365 4.916575 3.163367 4.337365
289 290 291 292 293 294 295 296
4.459570 4.435544 4.337365 5.175560 5.915874 3.774390 2.689453 4.576581
297 298 299 300 301 302 303 304
4.459570 6.559693 4.666451 6.647247 4.197766 6.150798 3.173843 6.063883
305 306 307 308 309 310 311 312
3.726860 4.087853 3.978539 2.222216 3.804545 4.183865 3.321853 7.059141
313 314 315 316 317 318 319 320
4.459570 4.815727 6.792023 4.625036 3.989015 3.630848 4.287029 3.940341
321 322 323 324 325 326 327 328
4.337365 4.050236 2.177786 3.283756 4.287029 3.684508 4.209968 3.576358
329 330 331 332 333 334 335 336
3.684508 6.494993 4.386870 6.368896 4.175403 2.901011 4.261550 3.915693
337 338 339 340 341 342 343 344
3.865772 4.131037 4.483388 4.411311 6.011886 4.769306 4.819227 3.890836
345 346 347 348 349 350 351 352
5.718857 6.416062 4.576581 5.149873 4.022887 6.494993 4.553594 5.201040
353 354 355 356 357 358 359 360
3.737336 4.386870 6.520888 5.985575 6.287590 4.022887 2.838953 3.890836
361 362 363 364 365 366 367 368
4.209968 6.214891 5.071565 4.131037 4.530400 3.306434 3.763439 6.165386
369 370 371 372 373 374 375 376
6.696337 6.125526 4.779782 3.737336 5.149873 3.940341 2.634791 3.684508
377 378 379 380 381 382 383 384
4.534382 5.565356 4.077377 2.077196 5.539046 4.804846 3.940341 3.001682
385 386 387 388 389 390 391 392
4.107065 5.841061 2.716838 4.287029 5.201040 4.599360 1.148806 5.261852
393 394 395 396 397 398 399 400
3.815021 6.442580 5.349555 4.534382 1.667948 5.693793 5.251375 5.782326
401 402 403 404 405 406 407 408
5.018321 1.748338 4.881576 4.050236 4.506998 4.483388 4.459570 4.077377
409 410 411 412 413 414 415 416
4.013041 2.433530 3.890836 6.468891 3.865772 4.576581 4.909340 4.452335
417 418 419 420 421 422 423 424
5.888732 1.802828 4.060469 3.332329 4.312301 4.209968 6.175862 2.662348
425 426 427 428 429 430 431 432
4.506998 4.987405 4.337365 4.157555 NA NA NA NA
433 434 435 436 437 438 439 440
NA NA NA NA NA NA NA NA
441 442 443 444 445 446 447 448
NA NA NA NA NA NA NA NA
449 450 451 452 453 454 455 456
NA NA NA NA NA NA NA NA
457 458 459 460 461 462 463 464
NA NA NA NA NA NA NA NA
465 466 467 468 469 470 471 472
NA NA NA NA NA NA NA NA
473 474 475 476 477 478 479 480
NA NA NA NA NA NA NA NA
481 482 483 484 485 486 487 488
NA NA NA NA NA NA NA NA
489 490 491 492 493 494 495 496
NA NA NA NA NA NA NA NA
497 498 499 500 501 502 503 504
NA NA NA NA NA NA NA NA
505 506 507 508 509 510 511 512
NA NA NA NA NA NA NA NA
513 514 515 516 517 518 519 520
NA NA NA NA NA NA NA NA
521 522 523 524 525 526 527 528
NA NA NA NA NA NA NA NA
529 530 531 532 533 534 535 536
NA NA NA NA NA NA NA NA
537 538 539 540 541 542 543 544
NA NA NA NA NA NA NA NA
545 546 547 548 549 550 551 552
NA NA NA NA NA NA NA NA
553 554 555 556 557 558 559 560
NA NA NA NA NA NA NA NA
561 562 563 564 565 566 567 568
NA NA NA NA NA NA NA NA
569 570 571 572 573 574 575 576
NA NA NA NA NA NA NA NA
577 578 579 580 581 582 583 584
NA NA NA NA NA NA NA NA
585 586 587 588 589 590 591 592
NA NA NA NA NA NA NA NA
593 594 595 596 597 598 599 600
NA NA NA NA NA NA NA NA
601 602 603 604 605 606 607 608
NA NA NA NA NA NA NA NA
609 610 611 612 613 614 615 616
NA NA NA NA NA NA NA NA
617 618 619 620 621 622 623 624
NA NA NA NA NA NA NA NA
625 626 627 628 629 630 631 632
NA NA NA NA NA NA NA NA
633 634 635 636 637 638 639 640
NA NA NA NA NA NA NA NA
641 642 643 644 645 646 647 648
NA NA NA NA NA NA NA NA
649 650 651 652 653 654 655 656
NA NA NA NA NA NA NA NA
657 658 659 660 661 662 663 664
NA NA NA NA NA NA NA NA
665 666 667 668 669 670 671 672
NA NA NA NA NA NA NA NA
673 674 675 676 677 678 679 680
NA NA NA NA NA NA NA NA
681 682 683 684 685 686 687 688
NA NA NA NA NA NA NA NA
689 690 691 692 693 694 695 696
NA NA NA NA NA NA NA NA
697 698 699 700 701 702 703 704
NA NA NA NA NA NA NA NA
705 706 707 708 709 710 711 712
NA NA NA NA NA NA NA NA
713 714 715 716 717 718 719 720
NA NA NA NA NA NA NA NA
721 722 723 724 725 726 727 728
NA NA NA NA NA NA NA NA
729 730 731 732 733 734 735 736
NA NA NA NA NA NA NA NA
737 738 739 740 741 742 743 744
NA NA NA NA NA NA NA NA
745 746 747 748 749 750 751 752
NA NA NA NA NA NA NA NA
753
NA
E[yo|ys=0] E[yo|ys=1]
1 4.241346 3.5861105
2 4.444623 3.7898561
3 4.292050 3.6345252
4 4.034724 3.3795056
5 5.483393 4.8203420
6 5.113886 4.4591369
7 6.136944 5.4517826
8 4.708073 4.0533509
9 4.450065 3.7954473
10 4.442262 3.7840639
11 4.298575 3.6402341
12 3.793205 3.1373588
13 3.851905 3.1973406
14 4.698726 4.0427178
15 3.549541 2.8949575
16 4.100499 3.4454263
17 4.847442 4.1911993
18 4.510819 3.8528776
19 5.030537 4.3509302
20 4.138634 3.4812449
21 5.986221 5.2987969
22 4.270028 3.5968678
23 5.369887 4.6901565
24 4.382484 3.7059658
25 4.413503 3.7588536
26 7.314490 6.6188970
27 4.961859 4.2929169
28 4.575398 3.9190290
29 6.490578 5.8052025
30 4.210654 3.5235079
31 4.662207 4.0057638
32 6.412261 5.7576851
33 4.809905 4.1467125
34 4.620115 3.9627987
35 6.939552 6.2629018
36 3.403883 2.7491310
37 4.881455 4.2039368
38 3.600476 2.9444603
39 5.505874 4.8308050
40 7.192049 6.4375486
41 3.880132 3.2255625
42 4.621954 3.9648682
43 6.421178 5.7460203
44 4.111946 3.4573699
45 4.019005 3.3643897
46 3.980607 3.3254146
47 6.496700 5.8291767
48 4.557579 3.8789756
49 4.341817 3.6806498
50 4.002793 3.3481377
51 4.643926 3.9882692
52 5.005887 4.3432271
53 4.291024 3.6336192
54 2.849801 2.1899621
55 3.749144 3.0943839
56 6.633401 5.9054601
57 6.161066 5.5016485
58 7.207690 6.4288215
59 6.116336 5.4574888
60 4.500867 3.8440648
61 5.393497 4.7170808
62 4.605283 3.9485228
63 2.764387 2.1098225
64 4.809436 4.1383582
65 4.650773 3.9945581
66 2.408934 1.7486020
67 6.649630 5.9710083
68 4.755571 4.0703685
69 4.597364 3.9384046
70 4.406994 3.7488755
71 4.784465 4.0980854
72 4.713164 4.0521017
73 3.513076 2.8301597
74 3.659540 3.0046795
75 4.649377 3.9947048
76 4.781428 4.1268416
77 3.929742 3.2743294
78 7.418694 6.7087348
79 6.007407 5.3413366
80 4.406603 3.7482786
81 2.041882 1.3793668
82 5.419999 4.7546888
83 4.533086 3.8773040
84 5.401953 4.7462958
85 3.166545 2.5106302
86 7.340761 6.6842097
87 5.543559 4.8802937
88 3.348827 2.6877794
89 6.027449 5.3491949
90 4.240021 3.5827404
91 4.759053 4.1020020
92 4.620980 3.9651295
93 4.747163 4.0885452
94 4.464080 3.8094888
95 4.213050 3.5579903
96 4.429185 3.7742202
97 4.940881 4.2846158
98 4.879434 4.2185946
99 4.151819 3.4751467
100 4.441007 3.7787435
101 4.391055 3.7344218
102 4.284411 3.6245338
103 4.547760 3.8930691
104 6.615856 5.9187695
105 4.135434 3.4784028
106 4.980423 4.3207299
107 3.990861 3.3228650
108 4.513506 3.8588067
109 4.826065 4.1695954
110 4.438687 3.7795766
111 6.920094 6.2403082
112 5.956450 5.2989686
113 6.611897 5.9339456
114 7.159544 6.3940591
115 4.758395 4.0981080
116 4.421406 3.7613019
117 5.123452 4.4554021
118 4.576090 3.9196557
119 6.932693 6.1742939
120 3.685355 3.0215838
121 5.190269 4.5316544
122 4.121983 3.4439255
123 3.968227 3.3119418
124 6.155236 5.4802718
125 7.105530 6.3559587
126 4.337469 3.6803628
127 6.371729 5.6953466
128 4.272827 3.6171531
129 5.964951 5.3103656
130 2.162378 1.5046087
131 3.864718 3.2098244
132 3.840721 3.1860969
133 4.605921 3.9490957
134 5.077674 4.4092053
135 3.898938 3.2443469
136 4.410629 3.7560349
137 4.527517 3.8671805
138 5.787096 5.1184488
139 4.415593 3.7592310
140 4.954320 4.2887965
141 5.039676 4.3796618
142 7.574419 6.8322880
143 5.891447 5.2259409
144 4.473789 3.8155342
145 3.188272 2.5325331
146 4.487518 3.8318915
147 4.601694 3.9469329
148 4.742616 4.0807867
149 5.649717 4.9951586
150 6.741903 6.0537161
151 6.706479 6.0076702
152 6.079939 5.4088204
153 4.531266 3.8740459
154 6.455310 5.7852055
155 7.064920 6.3085048
156 6.977577 6.2871817
157 3.967765 3.3130970
158 7.058444 6.3119314
159 4.951795 4.2954899
160 4.631892 3.9750370
161 4.348213 3.6932329
162 6.551366 5.8592352
163 5.799489 5.1335317
164 6.185898 5.5093060
165 5.009442 4.3291736
166 3.049813 2.3933236
167 7.478715 6.7272274
168 5.856080 5.1356968
169 4.490327 3.8344875
170 4.279190 3.6034399
171 3.461390 2.8065618
172 4.764473 4.0967554
173 4.574713 3.9199918
174 3.847482 3.1819142
175 4.654637 3.9980587
176 1.282470 0.6235064
177 6.637986 5.9550815
178 4.003708 3.3257191
179 4.044014 3.3888940
180 4.608250 3.9532195
181 5.566307 4.8964792
182 4.118567 3.4621812
183 4.653854 3.9991514
184 5.576978 4.9043647
185 4.412121 3.7528974
186 3.287225 2.6312684
187 6.851080 6.0877689
188 5.045281 4.3907327
189 4.071552 3.4156126
190 4.655304 3.9847124
191 4.349210 3.6945601
192 3.709646 3.0543440
193 4.540416 3.8847847
194 3.225570 2.5684474
195 4.944647 4.2818946
196 4.549675 3.8900215
197 4.396255 3.7378705
198 4.741956 4.0802445
199 5.194260 4.5333627
200 6.399757 5.7045381
201 4.624313 3.9607710
202 6.498837 5.8067500
203 7.079132 6.3296087
204 4.234693 3.5797926
205 4.638282 3.9779572
206 2.919005 2.2608922
207 4.705453 4.0488273
208 4.308619 3.6519749
209 5.203784 4.5125684
210 4.366392 3.6694608
211 4.978999 4.3176692
212 4.044820 3.3888980
213 4.584078 3.9268127
214 3.152610 2.4586785
215 4.533038 3.8773266
216 6.106131 5.3916860
217 4.454700 3.7970607
218 3.791657 3.1370666
219 5.023352 4.3459496
220 2.949301 2.2945362
221 5.028648 4.3738830
222 4.554130 3.8992163
223 4.146885 3.4716531
224 4.197129 3.5388898
225 6.719815 6.0390888
226 6.935085 6.2408196
227 4.538323 3.8802568
228 6.843967 6.1429555
229 4.970939 4.3109397
230 3.995787 3.3394634
231 4.195297 3.5372933
232 2.594847 1.9356306
233 4.161813 3.5067777
234 4.842471 4.1863582
235 4.382791 3.7259976
236 4.548348 3.8888941
237 2.411315 1.7375024
238 4.812572 4.1580196
239 7.072668 6.3650298
240 7.290529 6.5853981
241 4.836276 4.1705255
242 5.140085 4.4798181
243 4.624499 3.9683545
244 4.503170 3.8461238
245 4.579584 3.9246884
246 4.001029 3.3441908
247 2.926345 2.2678526
248 3.739165 3.0843793
249 4.455278 3.7952079
250 6.506949 5.8297855
251 4.989428 4.3162571
252 1.979617 1.3110261
253 6.820677 6.1208733
254 4.901825 4.2452635
255 4.583945 3.9266946
256 4.276362 3.6161029
257 4.998797 4.3359510
258 4.824501 4.1606419
259 3.936568 3.2775560
260 3.721649 3.0670807
261 4.414025 3.7578061
262 7.013194 6.3285757
263 6.185491 5.5191580
264 6.527561 5.8438633
265 3.288060 2.6017261
266 3.943951 3.2893857
267 4.612026 3.9545246
268 4.479703 3.8222913
269 5.494879 4.8294870
270 5.911652 5.2311039
271 5.710734 5.0542479
272 2.410789 1.7551092
273 1.780610 1.0997047
274 3.912212 3.2560268
275 4.241750 3.5428981
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393 394 395 396 397 398 399 400
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401 402 403 404 405 406 407 408
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481 482 483 484 485 486 487 488
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497 498 499 500 501 502 503 504
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513 514 515 516 517 518 519 520
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521 522 523 524 525 526 527 528
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529 530 531 532 533 534 535 536
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537 538 539 540 541 542 543 544
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553 554 555 556 557 558 559 560
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561 562 563 564 565 566 567 568
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569 570 571 572 573 574 575 576
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577 578 579 580 581 582 583 584
0.5197531 0.5303594 0.6578449 0.4882648 0.5735529 0.6424426 0.4374826 0.6813337
585 586 587 588 589 590 591 592
0.6824421 0.1725191 0.5657895 0.6771594 0.5509830 0.5872493 0.4328931 0.5896577
593 594 595 596 597 598 599 600
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601 602 603 604 605 606 607 608
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609 610 611 612 613 614 615 616
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617 618 619 620 621 622 623 624
0.3232265 0.6073500 0.5444139 0.4608040 0.5457977 0.5217353 0.5282302 0.4704401
625 626 627 628 629 630 631 632
0.5159969 0.6523100 0.5676801 0.6108556 0.4228495 0.5958439 0.2007842 0.4170508
633 634 635 636 637 638 639 640
0.5573828 0.6310680 0.5151196 0.7093301 0.5471639 0.3499527 0.5125493 0.1609934
641 642 643 644 645 646 647 648
0.6765161 0.5904605 0.3741191 0.6973434 0.6170274 0.6792626 0.8569659 0.6406652
649 650 651 652 653 654 655 656
0.6350228 0.2080993 0.5898861 0.5201982 0.5159273 0.5849333 0.5789706 0.3751475
657 658 659 660 661 662 663 664
0.6679178 0.3309873 0.6654611 0.4003700 0.4600312 0.6746497 0.4711603 0.5145312
665 666 667 668 669 670 671 672
0.6142318 0.4730765 0.6523223 0.5017336 0.5565380 0.4697832 0.4975482 0.6954920
673 674 675 676 677 678 679 680
0.4981477 0.4522318 0.6600458 0.6050575 0.2832260 0.6341774 0.6092006 0.8271045
681 682 683 684 685 686 687 688
0.3875321 0.4590480 0.7701868 0.5144153 0.6055840 0.5699064 0.6316344 0.6339549
689 690 691 692 693 694 695 696
0.3632363 0.4430689 0.5645229 0.6229264 0.6080875 0.6575720 0.5797677 0.5428814
697 698 699 700 701 702 703 704
0.6059058 0.5456522 0.6877347 0.5539068 0.4255091 0.3314323 0.6123712 0.5258183
705 706 707 708 709 710 711 712
0.5485294 0.3540187 0.4343883 0.7159345 0.5499973 0.5386473 0.5255142 0.4984409
713 714 715 716 717 718 719 720
0.5243771 0.3364618 0.7052032 0.5920626 0.5790450 0.5744355 0.5029695 0.3840295
721 722 723 724 725 726 727 728
0.5839930 0.6044318 0.6559484 0.5553156 0.2051587 0.2242671 0.4266476 0.6935754
729 730 731 732 733 734 735 736
0.6829475 0.6041711 0.6661603 0.4977747 0.3666543 0.6969443 0.6487802 0.5168696
737 738 739 740 741 742 743 744
0.5751670 0.6042553 0.6592254 0.6510552 0.4942161 0.5934895 0.4536989 0.3793843
745 746 747 748 749 750 751 752
0.5039410 0.5519400 0.4376660 0.5422957 0.6312674 0.5078106 0.7051200 0.3210352
753
0.4845593
3 4 5 6 7 8 9
3.915693 3.684508 5.071565 4.774115 5.643041 4.369198 4.130052
sampleSelection documentation built on Dec. 15, 2020, 3:01 a.m.
R Package Documentation
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Description Usage Arguments Value Author(s) See Also Examples
View source: R/predict.selection.R
Description
Calculate predicted values for sample selection models
fitted with function selection.
Usage
1 2 3 4 5 |
Arguments
object |
a fitted object of class |
newdata |
optionally, a data frame in which to look for variables with which to predict. If omitted, the fitted linear predictors or the fitted response values are returned. |
part |
character string indicating for which equation
the predicted variables should be calculated:
|
type |
if argument |
... |
further arguments (currently ignored). |
Value
In most cases, a numeric vector of the predicted values is returned. However, there are three exceptions: (i) when predicting the unconditional expectations of a Tobit-5 model, a matrix with two columns is returned, where the two columns correspond to the two outcome equations (E[yo1] and E[yo2]); (ii) when predicting the conditional expectations of a Tobit-2 model, a matrix with two columns is returned, where the first column returns the expectations conditional on the observation being not selected (E[yo|ys=0]), while the second column returns the expectations conditional on the observation being selected (E[yo|ys=1]); (iii) when predicting the conditional expectations of a Tobit-5 model, a matrix with four columns is returned, where the first two columns return the conditional expectations of the first outcome equation (E[yo1|ys=0] and E[yo1|ys=1]) and the last two columns return the conditional expectations of the second outcome equation (E[yo2|ys=0] and E[yo2|ys=1]).
Author(s)
Arne Henningsen and ‘fg nu’ (the code is partly based on the code posted by ‘fg nu’ at https://stackoverflow.com/questions/14005788/predict-function-for-heckman-model)
See Also
selection, predict,
predict.probit, residuals.selection,
and selection-methods.
Examples
1 2 3 4 5 6 7 8 9 10 11 12 13 | ## Greene( 2003 ): example 22.8, page 786
data( Mroz87 )
Mroz87$kids <- ( Mroz87$kids5 + Mroz87$kids618 > 0 )
# ML estimation
m <- selection( lfp ~ age + I( age^2 ) + faminc + kids + educ,
wage ~ exper + I( exper^2 ) + educ + city, Mroz87 )
predict( m )
predict( m, type = "conditional" )
predict( m, type = "link" )
predict( m, type = "response" )
predict( m, newdata = Mroz87[ 3:9, ] )
|
Example output
Loading required package: maxLik
Loading required package: miscTools
Please cite the 'maxLik' package as:
Henningsen, Arne and Toomet, Ott (2011). maxLik: A package for maximum likelihood estimation in R. Computational Statistics 26(3), 443-458. DOI 10.1007/s00180-010-0217-1.
If you have questions, suggestions, or comments regarding the 'maxLik' package, please use a forum or 'tracker' at maxLik's R-Forge site:
https://r-forge.r-project.org/projects/maxlik/
1 2 3 4 5 6 7 8
3.890836 4.104311 3.915693 3.684508 5.071565 4.774115 5.643041 4.369198
9 10 11 12 13 14 15 16
4.130052 4.060469 3.915693 3.433831 3.521037 4.337365 3.217026 3.752963
17 18 19 20 21 22 23 24
4.483388 4.131037 4.553594 3.763439 5.485802 3.815021 4.892549 3.915693
25 26 27 28 29 30 31 32
4.077377 6.792023 4.731673 4.209968 5.996051 3.711026 4.295993 6.089570
33 34 35 36 37 38 39 40
4.397346 4.337365 6.472316 3.064032 4.411311 3.305912 5.044062 6.546575
41 42 43 44 45 46 47 48
3.548801 4.337365 5.959057 3.789334 3.684508 3.630848 6.063883 4.083871
49 50 51 52 53 54 55 56
3.940341 3.684508 4.287029 4.752998 3.915693 2.583291 3.434486 6.037988
57 58 59 60 61 62 63 64
5.770518 6.520888 5.729737 4.131037 4.927051 4.235863 2.433530 4.362222
65 66 67 68 69 70 71 72
4.287029 2.012480 6.175862 4.261550 4.209968 4.130052 4.287029 4.312301
73 74 75 76 77 78 79 80
3.317384 3.347540 4.312301 4.459570 3.576358 6.861607 5.580983 4.131037
81 82 83 84 85 86 87 88
1.788369 5.177621 4.235863 5.045047 2.870855 6.973425 5.293226 3.088555
89 90 91 92 93 94 95 96
5.554880 3.865772 4.386870 4.261550 4.362222 4.131037 3.865772 4.083871
97 98 99 100 101 102 103 104
4.576581 4.479892 3.684508 4.033363 4.022887 3.890836 4.209968 6.089570
105 106 107 108 109 110 111 112
3.763439 4.588042 3.556036 4.175403 4.459570 4.050236 6.442580 5.580462
113 114 115 116 117 118 119 120
6.140322 6.494993 4.362222 4.026382 4.688400 4.209968 6.280356 3.269855
121 122 123 124 125 126 127 128
4.916575 3.650060 3.603707 5.693793 6.468891 3.964782 5.905398 3.915693
129 130 131 132 133 134 135 136
5.643041 1.883005 3.521037 3.521037 4.235863 4.640870 3.565882 4.077377
137 138 139 140 141 142 143 144
4.131037 5.349555 4.050236 4.530400 4.774115 6.951477 5.467605 4.197766
145 146 147 148 149 150 151 152
2.890535 4.131037 4.261550 4.337365 5.325321 6.239332 6.175862 5.632565
153 154 155 156 157 158 159 160
4.157555 6.011886 6.416062 6.468891 3.630848 6.427381 4.587057 4.261550
161 162 163 164 165 166 167 168
4.002565 6.037988 5.373580 5.718857 4.530400 2.760021 6.838620 5.276232
169 170 171 172 173 174 175 176
4.131037 3.815021 3.119353 4.530400 4.235863 3.423355 4.287029 1.010932
177 178 179 180 181 182 183 184
6.150798 3.532010 3.737336 4.261550 5.123978 3.752963 4.337365 5.123978
185 186 187 188 189 190 191 192
4.022887 2.926490 6.190242 4.718555 3.711026 4.209968 4.013041 3.358016
193 194 195 196 197 198 199 200
4.183865 2.941286 4.534382 4.157555 4.013041 4.337365 4.794370 5.878256
201 202 203 204 205 206 207 208
4.209968 5.985575 6.442580 3.890836 4.241871 2.642025 4.337365 3.940341
209 210 211 212 213 214 215 216
4.692868 3.840500 4.576581 3.684508 4.209968 2.976826 4.175403 5.539046
217 218 219 220 221 222 223 224
4.077377 3.458688 4.553594 2.634791 4.688400 4.209968 3.684508 3.815021
225 226 227 228 229 230 231 232
6.239332 6.416062 4.157555 6.307912 4.576581 3.630848 3.815021 2.324811
233 234 235 236 237 238 239 240
3.815021 4.479892 4.013041 4.157555 2.194867 4.483388 6.520888 6.744595
241 242 243 244 245 246 247 248
4.411311 4.744035 4.261550 4.131037 4.235863 3.630848 2.651872 3.398291
249 250 251 252 253 254 255 256
4.060469 6.037988 4.534382 1.748338 6.287590 4.534382 4.209968 3.880360
257 258 259 260 261 262 263 264
4.588042 4.576581 3.548801 3.398291 4.050236 6.520888 5.757886 6.037988
265 266 267 268 269 270 271 272
3.099031 3.620372 4.235863 4.104311 5.071565 5.431727 5.344068 2.112321
273 274 275 276 277 278 279 280
1.580747 3.548801 3.711026 5.276232 4.235863 3.576358 4.459570 5.513371
281 282 283 284 285 286 287 288
6.427381 4.157555 4.362222 4.261550 5.056365 4.916575 3.163367 4.337365
289 290 291 292 293 294 295 296
4.459570 4.435544 4.337365 5.175560 5.915874 3.774390 2.689453 4.576581
297 298 299 300 301 302 303 304
4.459570 6.559693 4.666451 6.647247 4.197766 6.150798 3.173843 6.063883
305 306 307 308 309 310 311 312
3.726860 4.087853 3.978539 2.222216 3.804545 4.183865 3.321853 7.059141
313 314 315 316 317 318 319 320
4.459570 4.815727 6.792023 4.625036 3.989015 3.630848 4.287029 3.940341
321 322 323 324 325 326 327 328
4.337365 4.050236 2.177786 3.283756 4.287029 3.684508 4.209968 3.576358
329 330 331 332 333 334 335 336
3.684508 6.494993 4.386870 6.368896 4.175403 2.901011 4.261550 3.915693
337 338 339 340 341 342 343 344
3.865772 4.131037 4.483388 4.411311 6.011886 4.769306 4.819227 3.890836
345 346 347 348 349 350 351 352
5.718857 6.416062 4.576581 5.149873 4.022887 6.494993 4.553594 5.201040
353 354 355 356 357 358 359 360
3.737336 4.386870 6.520888 5.985575 6.287590 4.022887 2.838953 3.890836
361 362 363 364 365 366 367 368
4.209968 6.214891 5.071565 4.131037 4.530400 3.306434 3.763439 6.165386
369 370 371 372 373 374 375 376
6.696337 6.125526 4.779782 3.737336 5.149873 3.940341 2.634791 3.684508
377 378 379 380 381 382 383 384
4.534382 5.565356 4.077377 2.077196 5.539046 4.804846 3.940341 3.001682
385 386 387 388 389 390 391 392
4.107065 5.841061 2.716838 4.287029 5.201040 4.599360 1.148806 5.261852
393 394 395 396 397 398 399 400
3.815021 6.442580 5.349555 4.534382 1.667948 5.693793 5.251375 5.782326
401 402 403 404 405 406 407 408
5.018321 1.748338 4.881576 4.050236 4.506998 4.483388 4.459570 4.077377
409 410 411 412 413 414 415 416
4.013041 2.433530 3.890836 6.468891 3.865772 4.576581 4.909340 4.452335
417 418 419 420 421 422 423 424
5.888732 1.802828 4.060469 3.332329 4.312301 4.209968 6.175862 2.662348
425 426 427 428 429 430 431 432
4.506998 4.987405 4.337365 4.157555 NA NA NA NA
433 434 435 436 437 438 439 440
NA NA NA NA NA NA NA NA
441 442 443 444 445 446 447 448
NA NA NA NA NA NA NA NA
449 450 451 452 453 454 455 456
NA NA NA NA NA NA NA NA
457 458 459 460 461 462 463 464
NA NA NA NA NA NA NA NA
465 466 467 468 469 470 471 472
NA NA NA NA NA NA NA NA
473 474 475 476 477 478 479 480
NA NA NA NA NA NA NA NA
481 482 483 484 485 486 487 488
NA NA NA NA NA NA NA NA
489 490 491 492 493 494 495 496
NA NA NA NA NA NA NA NA
497 498 499 500 501 502 503 504
NA NA NA NA NA NA NA NA
505 506 507 508 509 510 511 512
NA NA NA NA NA NA NA NA
513 514 515 516 517 518 519 520
NA NA NA NA NA NA NA NA
521 522 523 524 525 526 527 528
NA NA NA NA NA NA NA NA
529 530 531 532 533 534 535 536
NA NA NA NA NA NA NA NA
537 538 539 540 541 542 543 544
NA NA NA NA NA NA NA NA
545 546 547 548 549 550 551 552
NA NA NA NA NA NA NA NA
553 554 555 556 557 558 559 560
NA NA NA NA NA NA NA NA
561 562 563 564 565 566 567 568
NA NA NA NA NA NA NA NA
569 570 571 572 573 574 575 576
NA NA NA NA NA NA NA NA
577 578 579 580 581 582 583 584
NA NA NA NA NA NA NA NA
585 586 587 588 589 590 591 592
NA NA NA NA NA NA NA NA
593 594 595 596 597 598 599 600
NA NA NA NA NA NA NA NA
601 602 603 604 605 606 607 608
NA NA NA NA NA NA NA NA
609 610 611 612 613 614 615 616
NA NA NA NA NA NA NA NA
617 618 619 620 621 622 623 624
NA NA NA NA NA NA NA NA
625 626 627 628 629 630 631 632
NA NA NA NA NA NA NA NA
633 634 635 636 637 638 639 640
NA NA NA NA NA NA NA NA
641 642 643 644 645 646 647 648
NA NA NA NA NA NA NA NA
649 650 651 652 653 654 655 656
NA NA NA NA NA NA NA NA
657 658 659 660 661 662 663 664
NA NA NA NA NA NA NA NA
665 666 667 668 669 670 671 672
NA NA NA NA NA NA NA NA
673 674 675 676 677 678 679 680
NA NA NA NA NA NA NA NA
681 682 683 684 685 686 687 688
NA NA NA NA NA NA NA NA
689 690 691 692 693 694 695 696
NA NA NA NA NA NA NA NA
697 698 699 700 701 702 703 704
NA NA NA NA NA NA NA NA
705 706 707 708 709 710 711 712
NA NA NA NA NA NA NA NA
713 714 715 716 717 718 719 720
NA NA NA NA NA NA NA NA
721 722 723 724 725 726 727 728
NA NA NA NA NA NA NA NA
729 730 731 732 733 734 735 736
NA NA NA NA NA NA NA NA
737 738 739 740 741 742 743 744
NA NA NA NA NA NA NA NA
745 746 747 748 749 750 751 752
NA NA NA NA NA NA NA NA
753
NA
E[yo|ys=0] E[yo|ys=1]
1 4.241346 3.5861105
2 4.444623 3.7898561
3 4.292050 3.6345252
4 4.034724 3.3795056
5 5.483393 4.8203420
6 5.113886 4.4591369
7 6.136944 5.4517826
8 4.708073 4.0533509
9 4.450065 3.7954473
10 4.442262 3.7840639
11 4.298575 3.6402341
12 3.793205 3.1373588
13 3.851905 3.1973406
14 4.698726 4.0427178
15 3.549541 2.8949575
16 4.100499 3.4454263
17 4.847442 4.1911993
18 4.510819 3.8528776
19 5.030537 4.3509302
20 4.138634 3.4812449
21 5.986221 5.2987969
22 4.270028 3.5968678
23 5.369887 4.6901565
24 4.382484 3.7059658
25 4.413503 3.7588536
26 7.314490 6.6188970
27 4.961859 4.2929169
28 4.575398 3.9190290
29 6.490578 5.8052025
30 4.210654 3.5235079
31 4.662207 4.0057638
32 6.412261 5.7576851
33 4.809905 4.1467125
34 4.620115 3.9627987
35 6.939552 6.2629018
36 3.403883 2.7491310
37 4.881455 4.2039368
38 3.600476 2.9444603
39 5.505874 4.8308050
40 7.192049 6.4375486
41 3.880132 3.2255625
42 4.621954 3.9648682
43 6.421178 5.7460203
44 4.111946 3.4573699
45 4.019005 3.3643897
46 3.980607 3.3254146
47 6.496700 5.8291767
48 4.557579 3.8789756
49 4.341817 3.6806498
50 4.002793 3.3481377
51 4.643926 3.9882692
52 5.005887 4.3432271
53 4.291024 3.6336192
54 2.849801 2.1899621
55 3.749144 3.0943839
56 6.633401 5.9054601
57 6.161066 5.5016485
58 7.207690 6.4288215
59 6.116336 5.4574888
60 4.500867 3.8440648
61 5.393497 4.7170808
62 4.605283 3.9485228
63 2.764387 2.1098225
64 4.809436 4.1383582
65 4.650773 3.9945581
66 2.408934 1.7486020
67 6.649630 5.9710083
68 4.755571 4.0703685
69 4.597364 3.9384046
70 4.406994 3.7488755
71 4.784465 4.0980854
72 4.713164 4.0521017
73 3.513076 2.8301597
74 3.659540 3.0046795
75 4.649377 3.9947048
76 4.781428 4.1268416
77 3.929742 3.2743294
78 7.418694 6.7087348
79 6.007407 5.3413366
80 4.406603 3.7482786
81 2.041882 1.3793668
82 5.419999 4.7546888
83 4.533086 3.8773040
84 5.401953 4.7462958
85 3.166545 2.5106302
86 7.340761 6.6842097
87 5.543559 4.8802937
88 3.348827 2.6877794
89 6.027449 5.3491949
90 4.240021 3.5827404
91 4.759053 4.1020020
92 4.620980 3.9651295
93 4.747163 4.0885452
94 4.464080 3.8094888
95 4.213050 3.5579903
96 4.429185 3.7742202
97 4.940881 4.2846158
98 4.879434 4.2185946
99 4.151819 3.4751467
100 4.441007 3.7787435
101 4.391055 3.7344218
102 4.284411 3.6245338
103 4.547760 3.8930691
104 6.615856 5.9187695
105 4.135434 3.4784028
106 4.980423 4.3207299
107 3.990861 3.3228650
108 4.513506 3.8588067
109 4.826065 4.1695954
110 4.438687 3.7795766
111 6.920094 6.2403082
112 5.956450 5.2989686
113 6.611897 5.9339456
114 7.159544 6.3940591
115 4.758395 4.0981080
116 4.421406 3.7613019
117 5.123452 4.4554021
118 4.576090 3.9196557
119 6.932693 6.1742939
120 3.685355 3.0215838
121 5.190269 4.5316544
122 4.121983 3.4439255
123 3.968227 3.3119418
124 6.155236 5.4802718
125 7.105530 6.3559587
126 4.337469 3.6803628
127 6.371729 5.6953466
128 4.272827 3.6171531
129 5.964951 5.3103656
130 2.162378 1.5046087
131 3.864718 3.2098244
132 3.840721 3.1860969
133 4.605921 3.9490957
134 5.077674 4.4092053
135 3.898938 3.2443469
136 4.410629 3.7560349
137 4.527517 3.8671805
138 5.787096 5.1184488
139 4.415593 3.7592310
140 4.954320 4.2887965
141 5.039676 4.3796618
142 7.574419 6.8322880
143 5.891447 5.2259409
144 4.473789 3.8155342
145 3.188272 2.5325331
146 4.487518 3.8318915
147 4.601694 3.9469329
148 4.742616 4.0807867
149 5.649717 4.9951586
150 6.741903 6.0537161
151 6.706479 6.0076702
152 6.079939 5.4088204
153 4.531266 3.8740459
154 6.455310 5.7852055
155 7.064920 6.3085048
156 6.977577 6.2871817
157 3.967765 3.3130970
158 7.058444 6.3119314
159 4.951795 4.2954899
160 4.631892 3.9750370
161 4.348213 3.6932329
162 6.551366 5.8592352
163 5.799489 5.1335317
164 6.185898 5.5093060
165 5.009442 4.3291736
166 3.049813 2.3933236
167 7.478715 6.7272274
168 5.856080 5.1356968
169 4.490327 3.8344875
170 4.279190 3.6034399
171 3.461390 2.8065618
172 4.764473 4.0967554
173 4.574713 3.9199918
174 3.847482 3.1819142
175 4.654637 3.9980587
176 1.282470 0.6235064
177 6.637986 5.9550815
178 4.003708 3.3257191
179 4.044014 3.3888940
180 4.608250 3.9532195
181 5.566307 4.8964792
182 4.118567 3.4621812
183 4.653854 3.9991514
184 5.576978 4.9043647
185 4.412121 3.7528974
186 3.287225 2.6312684
187 6.851080 6.0877689
188 5.045281 4.3907327
189 4.071552 3.4156126
190 4.655304 3.9847124
191 4.349210 3.6945601
192 3.709646 3.0543440
193 4.540416 3.8847847
194 3.225570 2.5684474
195 4.944647 4.2818946
196 4.549675 3.8900215
197 4.396255 3.7378705
198 4.741956 4.0802445
199 5.194260 4.5333627
200 6.399757 5.7045381
201 4.624313 3.9607710
202 6.498837 5.8067500
203 7.079132 6.3296087
204 4.234693 3.5797926
205 4.638282 3.9779572
206 2.919005 2.2608922
207 4.705453 4.0488273
208 4.308619 3.6519749
209 5.203784 4.5125684
210 4.366392 3.6694608
211 4.978999 4.3176692
212 4.044820 3.3888980
213 4.584078 3.9268127
214 3.152610 2.4586785
215 4.533038 3.8773266
216 6.106131 5.3916860
217 4.454700 3.7970607
218 3.791657 3.1370666
219 5.023352 4.3459496
220 2.949301 2.2945362
221 5.028648 4.3738830
222 4.554130 3.8992163
223 4.146885 3.4716531
224 4.197129 3.5388898
225 6.719815 6.0390888
226 6.935085 6.2408196
227 4.538323 3.8802568
228 6.843967 6.1429555
229 4.970939 4.3109397
230 3.995787 3.3394634
231 4.195297 3.5372933
232 2.594847 1.9356306
233 4.161813 3.5067777
234 4.842471 4.1863582
235 4.382791 3.7259976
236 4.548348 3.8888941
237 2.411315 1.7375024
238 4.812572 4.1580196
239 7.072668 6.3650298
240 7.290529 6.5853981
241 4.836276 4.1705255
242 5.140085 4.4798181
243 4.624499 3.9683545
244 4.503170 3.8461238
245 4.579584 3.9246884
246 4.001029 3.3441908
247 2.926345 2.2678526
248 3.739165 3.0843793
249 4.455278 3.7952079
250 6.506949 5.8297855
251 4.989428 4.3162571
252 1.979617 1.3110261
253 6.820677 6.1208733
254 4.901825 4.2452635
255 4.583945 3.9266946
256 4.276362 3.6161029
257 4.998797 4.3359510
258 4.824501 4.1606419
259 3.936568 3.2775560
260 3.721649 3.0670807
261 4.414025 3.7578061
262 7.013194 6.3285757
263 6.185491 5.5191580
264 6.527561 5.8438633
265 3.288060 2.6017261
266 3.943951 3.2893857
267 4.612026 3.9545246
268 4.479703 3.8222913
269 5.494879 4.8294870
270 5.911652 5.2311039
271 5.710734 5.0542479
272 2.410789 1.7551092
273 1.780610 1.0997047
274 3.912212 3.2560268
275 4.241750 3.5428981
276 5.843043 5.1287230
277 4.621137 3.9624737
278 3.959636 3.3012431
279 4.984819 4.2881400
280 5.920028 5.2579454
281 6.868828 6.1992204
282 4.533568 3.8760837
283 4.714993 4.0596193
284 4.763649 4.0756298
285 5.495826 4.8267108
286 5.375952 4.7015752
287 3.601105 2.9324101
288 4.690639 4.0352335
289 4.860862 4.1997260
290 4.765251 4.1106953
291 4.831094 4.1459921
292 5.708042 5.0084827
293 6.467293 5.7598109
294 4.185263 3.5223946
295 2.979477 2.3230119
296 5.017710 4.3481817
297 4.860959 4.1998069
298 6.893970 6.2393583
299 5.111950 4.4413163
300 7.167482 6.4727514
301 4.671640 3.9929858
302 6.659358 5.9690091
303 3.517659 2.8627596
304 6.525769 5.8506785
305 4.083330 3.4277045
306 4.474160 3.8153536
307 4.333539 3.6780178
308 2.467243 1.8026408
309 4.199368 3.5392958
310 4.577776 3.9178466
311 3.615735 2.9596557
312 7.469563 6.8067805
313 4.857342 4.1967956
314 5.175452 4.5195775
315 7.264156 6.5860349
316 5.025396 4.3644193
317 4.444617 3.7712931
318 3.985032 3.3295659
319 4.800993 4.1086433
320 4.266378 3.6118281
321 4.816463 4.1361773
322 4.502915 3.8303882
323 2.461440 1.8042381
324 3.705248 3.0402445
325 4.618196 3.9636284
326 3.968858 3.3117429
327 4.505107 3.8491431
328 3.984310 3.3219893
329 4.046559 3.3904922
330 7.034304 6.3319513
331 4.767890 4.1097916
332 7.020177 6.2623817
333 4.461489 3.8045837
334 3.217581 2.5628809
335 4.601790 3.9470252
336 4.267562 3.6122450
337 4.352837 3.6699736
338 4.508212 3.8505905
339 4.871127 4.2121184
340 4.712395 4.0569153
341 6.467605 5.7942488
342 5.176119 4.5140073
343 5.241556 4.5763747
344 4.245951 3.5904217
345 6.202137 5.5205116
346 7.013223 6.2844122
347 5.057011 4.3763016
348 5.544908 4.8848026
349 4.206595 3.5173411
350 7.226410 6.4189414
351 5.052849 4.3658344
352 5.581091 4.9231156
353 4.110207 3.4530807
354 4.748609 4.0925688
355 7.043908 6.3481005
356 6.477517 5.7930222
357 6.950251 6.1858745
358 4.374986 3.7196546
359 3.109555 2.4504349
360 4.251644 3.5956817
361 4.595472 3.9367776
362 6.684902 6.0074231
363 5.517918 4.8470637
364 4.541585 3.8787788
365 4.865135 4.2105150
366 3.580322 2.9217376
367 4.134686 3.4777351
368 6.643641 5.9636217
369 7.276235 6.5558280
370 6.586341 5.9115568
371 5.243709 4.5680295
372 4.104191 3.4476863
373 5.565909 4.9020305
374 4.304248 3.6480182
375 2.928745 2.2726725
376 4.054427 3.3976154
377 4.912655 4.2549004
378 6.042662 5.3629413
379 4.478138 3.8170929
380 2.325842 1.6621644
381 6.003562 5.3277109
382 5.232017 4.5657809
383 4.430461 3.7465806
384 3.332405 2.6778418
385 4.473370 3.8169184
386 6.607127 5.7759203
387 3.026970 2.3720281
388 4.641666 3.9861698
389 5.731192 5.0325692
390 5.107167 4.4170930
391 1.345331 0.6628238
392 5.711276 5.0396192
393 4.223423 3.5610192
394 6.953306 6.2621606
395 5.800819 5.1286726
396 4.966836 4.2993970
397 1.851163 1.1616308
398 6.328263 5.5798861
399 5.642722 4.9831855
400 6.274659 5.5900316
401 5.454065 4.7858506
402 2.031943 1.3747354
403 5.348042 4.6716199
404 4.422936 3.7658277
405 4.885966 4.2281265
406 4.869756 4.2109409
407 4.832667 4.1755154
408 4.462017 3.8034407
409 4.516652 3.8280940
410 2.801264 2.1446735
411 4.260403 3.6036285
412 6.998519 6.3001057
413 4.214465 3.5593318
414 5.016490 4.3472645
415 5.363044 4.6902399
416 4.854437 4.1931621
417 6.435022 5.7297400
418 2.077012 1.4184742
419 4.432318 3.7753031
420 3.683995 3.0286907
421 4.618193 3.9630276
422 4.566980 3.9113148
423 6.664983 5.9814363
424 2.989017 2.3344688
425 4.911344 4.2496766
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7 8 9 10 11 12
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13 14 15 16 17 18
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19 20 21 22 23 24
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31 32 33 34 35 36
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61 62 63 64 65 66
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91 92 93 94 95 96
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103 104 105 106 107 108
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145 146 147 148 149 150
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157 158 159 160 161 162
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295 296 297 298 299 300
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403 404 405 406 407 408
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415 416 417 418 419 420
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433 434 435 436 437 438
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439 440 441 442 443 444
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445 446 447 448 449 450
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733 734 735 736 737 738
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17 18 19 20 21 22 23 24
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25 26 27 28 29 30 31 32
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33 34 35 36 37 38 39 40
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41 42 43 44 45 46 47 48
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49 50 51 52 53 54 55 56
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57 58 59 60 61 62 63 64
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65 66 67 68 69 70 71 72
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73 74 75 76 77 78 79 80
0.2865530 0.4764373 0.5148772 0.4916972 0.5391783 0.7846751 0.6402087 0.4185874
81 82 83 84 85 86 87 88
0.3826521 0.3643080 0.4532349 0.5443489 0.4508047 0.5594930 0.3774244 0.3937271
89 90 91 92 93 94 95 96
0.6967428 0.5693897 0.5664445 0.5480365 0.5844682 0.5087805 0.5301465 0.5272257
97 98 99 100 101 102 103 104
0.5551105 0.6045975 0.6906022 0.6155314 0.5606906 0.5964361 0.5159568 0.7549792
105 106 107 108 109 110 111 112
0.5661758 0.5947939 0.6509399 0.5164254 0.5582823 0.5893565 0.7024476 0.5718613
113 114 115 116 117 118 119 120
0.6955889 0.8681435 0.6000017 0.5984260 0.6512272 0.5577439 0.8601504 0.6259690
121 122 123 124 125 126 127 128
0.4155604 0.6959920 0.5554293 0.6836559 0.8493381 0.5671640 0.6894494 0.5446832
129 130 131 132 133 134 135 136
0.4917767 0.4247275 0.5247892 0.4883477 0.5634047 0.6534394 0.5088003 0.5090969
137 138 139 140 141 142 143 144
0.6004215 0.6543681 0.5566398 0.6369722 0.4023557 0.8393966 0.6368725 0.4193251
145 146 147 148 149 150 151 152
0.4540489 0.5437262 0.5194936 0.6123188 0.4955949 0.7302835 0.7593169 0.6666093
153 154 155 156 157 158 159 160
0.5686242 0.6617244 0.8578066 0.7368045 0.5146377 0.8453485 0.5557442 0.5638111
161 162 163 164 165 166 167 168
0.5277235 0.7417351 0.6395439 0.6902853 0.7041957 0.4414262 0.8517707 0.8049163
169 170 171 172 173 174 175 176
0.5478328 0.6868944 0.5223312 0.3505567 0.5175487 0.6372407 0.5598834 0.4120680
177 178 179 180 181 182 183 184
0.7134063 0.6957308 0.4681246 0.5292885 0.6603625 0.5569957 0.4834083 0.6734926
185 186 187 188 189 190 191 192
0.5904433 0.5499367 0.8657518 0.4991623 0.5496332 0.6640947 0.5135103 0.5365927
193 194 195 196 197 198 199 200
0.5438284 0.4326198 0.6190318 0.5944339 0.5820525 0.6114304 0.6050710 0.7501242
201 202 203 204 205 206 207 208
0.6244445 0.7416149 0.8492754 0.5250523 0.6003281 0.4208693 0.5605744 0.5608485
209 210 211 212 213 214 215 216
0.7391561 0.7545820 0.6084976 0.5493216 0.5691919 0.2533155 0.5454159 0.7937418
217 218 219 220 221 222 223 224
0.5737532 0.5086681 0.6934689 0.4803405 0.5196494 0.5255078 0.6847682 0.5805001
225 226 227 228 229 230 231 232
0.7058396 0.7475858 0.5786167 0.7646873 0.5975122 0.5560349 0.5779237 0.4096314
233 234 235 236 237 238 239 240
0.5294248 0.5526163 0.5629631 0.5926012 0.3212290 0.5029156 0.7797486 0.7742303
241 242 243 244 245 246 247 248
0.6383243 0.5998341 0.5531542 0.5663730 0.5248486 0.5635800 0.4168206 0.5205888
249 250 251 252 253 254 255 256
0.5981327 0.6925369 0.6759736 0.3459210 0.7617662 0.5596471 0.5690023 0.5997675
257 258 259 260 261 262 263 264
0.6196842 0.3734525 0.5884064 0.4940015 0.5543715 0.7190951 0.6417295 0.7160661
265 266 267 268 269 270 271 272
0.2754192 0.4943419 0.5721103 0.5710153 0.6361877 0.7052032 0.5585289 0.4552042
273 274 275 276 277 278 279 280
0.2935253 0.5538235 0.7594229 0.7934976 0.5849333 0.5821419 0.7539329 0.6142097
281 282 283 284 285 286 287 288
0.6592625 0.5718966 0.5382748 0.7297746 0.6567786 0.6811876 0.6546151 0.5390156
289 290 291 292 293 294 295 296
0.6069736 0.5037105 0.7206648 0.7611674 0.7794111 0.6198418 0.4417958 0.6588647
297 298 299 300 301 302 303 304
0.6071058 0.5106486 0.6642949 0.7488296 0.6982549 0.7366716 0.5249901 0.6841837
305 306 307 308 309 310 311 312
0.5437097 0.5863733 0.5415536 0.3686822 0.5981513 0.5968983 0.4479374 0.6192410
313 314 315 316 317 318 319 320
0.6021864 0.5484658 0.6962371 0.6057101 0.6766459 0.5403539 0.7423467 0.4981083
321 322 323 324 325 326 327 328
0.7042595 0.6731017 0.4316085 0.6338190 0.5059316 0.4327253 0.4499318 0.6159431
329 330 331 332 333 334 335 336
0.5518514 0.7678633 0.5789706 0.8594416 0.4355061 0.4835348 0.5196369 0.5369453
337 338 339 340 341 342 343 344
0.7132684 0.5735448 0.5883677 0.4593340 0.6767884 0.6144167 0.6349087 0.5417222
345 346 347 348 349 350 351 352
0.7090119 0.8193635 0.7057778 0.5984426 0.2665313 0.9058145 0.7267017 0.5776069
353 354 355 356 357 358 359 360
0.5674268 0.5513973 0.7516732 0.7186933 0.8669298 0.5372837 0.4105509 0.5500434
361 362 363 364 365 366 367 368
0.5852553 0.6937652 0.6653500 0.6194096 0.5113427 0.4158739 0.5651065 0.7032968
369 370 371 372 373 374 375 376
0.8049595 0.6829076 0.6866074 0.5588000 0.6266752 0.5545415 0.4480511 0.5632044
377 378 379 380 381 382 383 384
0.5750966 0.7022083 0.6062532 0.3746489 0.6873049 0.6411701 0.7166748 0.5052570
385 386 387 388 389 390 391 392
0.5580072 0.9216310 0.4735261 0.5410201 0.7588533 0.7358725 0.2879458 0.6691283
393 394 395 396 397 398 399 400
0.6165454 0.7389556 0.6713782 0.6479296 0.2657093 0.8477952 0.5933662 0.7191247
401 402 403 404 405 406 407 408
0.6521021 0.4315311 0.6896079 0.5671817 0.5760806 0.5864594 0.5677491 0.5840474
409 410 411 412 413 414 415 416
0.7313999 0.5600665 0.5626999 0.7583308 0.5322473 0.6573402 0.6743474 0.6080702
417 418 419 420 421 422 423 424
0.7745691 0.4163527 0.5659684 0.5366459 0.4668921 0.5445039 0.7155638 0.4990758
425 426 427 428 429 430 431 432
0.6111025 0.6261541 0.5764778 0.5111419 0.4704860 0.6703434 0.5220083 0.6074321
433 434 435 436 437 438 439 440
0.5395872 0.5619805 0.6270762 0.3015987 0.4052074 0.4947492 0.4786242 0.5355914
441 442 443 444 445 446 447 448
0.2717957 0.4774366 0.4628312 0.5323009 0.4618639 0.6390052 0.6195364 0.5465704
449 450 451 452 453 454 455 456
0.5574581 0.6892865 0.4172948 0.5438050 0.7809667 0.5667604 0.5507572 0.5308496
457 458 459 460 461 462 463 464
0.3152138 0.7047717 0.5508021 0.5222250 0.4382788 0.4551609 0.5293084 0.4204571
465 466 467 468 469 470 471 472
0.4935461 0.6890858 0.6085291 0.6253650 0.5168030 0.5082398 0.3478100 0.5484717
473 474 475 476 477 478 479 480
0.5345393 0.4867229 0.5723022 0.6437167 0.5432864 0.3988003 0.5501278 0.7099414
481 482 483 484 485 486 487 488
0.6891994 0.5534190 0.6354746 0.6829943 0.2335366 0.6188983 0.1847491 0.7829775
489 490 491 492 493 494 495 496
0.6097325 0.7677320 0.5895828 0.7349520 0.6898410 0.4911528 0.5315273 0.5520614
497 498 499 500 501 502 503 504
0.5192411 0.4478928 0.6205295 0.3865473 0.6275558 0.8390475 0.6936543 0.5711995
505 506 507 508 509 510 511 512
0.5867666 0.6688475 0.6212408 0.5573332 0.5689975 0.4528931 0.5289463 0.5788833
513 514 515 516 517 518 519 520
0.4892448 0.3426774 0.4981317 0.5685786 0.4181913 0.5882159 0.5875437 0.5768968
521 522 523 524 525 526 527 528
0.3562302 0.5622191 0.6517847 0.5433276 0.4195393 0.5479144 0.5179093 0.5638111
529 530 531 532 533 534 535 536
0.3407162 0.4094076 0.2987293 0.6726622 0.6226224 0.5241813 0.7276293 0.5657266
537 538 539 540 541 542 543 544
0.4512228 0.3146789 0.5678083 0.3479867 0.3554908 0.4454947 0.6769933 0.4713650
545 546 547 548 549 550 551 552
0.5311050 0.6285802 0.3954340 0.5529025 0.4381590 0.5006007 0.4677502 0.3587874
553 554 555 556 557 558 559 560
0.5495351 0.6202612 0.3919487 0.5340939 0.6360897 0.5452089 0.3930939 0.5142944
561 562 563 564 565 566 567 568
0.3329455 0.3257744 0.5415909 0.4948738 0.4337301 0.4532867 0.2794559 0.6997540
569 570 571 572 573 574 575 576
0.5745605 0.5229372 0.5423304 0.5489246 0.5272099 0.7484232 0.7150960 0.5748055
577 578 579 580 581 582 583 584
0.5197531 0.5303594 0.6578449 0.4882648 0.5735529 0.6424426 0.4374826 0.6813337
585 586 587 588 589 590 591 592
0.6824421 0.1725191 0.5657895 0.6771594 0.5509830 0.5872493 0.4328931 0.5896577
593 594 595 596 597 598 599 600
0.4320614 0.3706368 0.4730909 0.3571980 0.5566810 0.2752824 0.6149386 0.4313358
601 602 603 604 605 606 607 608
0.4864246 0.7145005 0.5619728 0.4893973 0.6009252 0.4887128 0.4867908 0.4886166
609 610 611 612 613 614 615 616
0.5277752 0.7780135 0.5814891 0.5440785 0.5164039 0.5731644 0.5328971 0.4489282
617 618 619 620 621 622 623 624
0.3232265 0.6073500 0.5444139 0.4608040 0.5457977 0.5217353 0.5282302 0.4704401
625 626 627 628 629 630 631 632
0.5159969 0.6523100 0.5676801 0.6108556 0.4228495 0.5958439 0.2007842 0.4170508
633 634 635 636 637 638 639 640
0.5573828 0.6310680 0.5151196 0.7093301 0.5471639 0.3499527 0.5125493 0.1609934
641 642 643 644 645 646 647 648
0.6765161 0.5904605 0.3741191 0.6973434 0.6170274 0.6792626 0.8569659 0.6406652
649 650 651 652 653 654 655 656
0.6350228 0.2080993 0.5898861 0.5201982 0.5159273 0.5849333 0.5789706 0.3751475
657 658 659 660 661 662 663 664
0.6679178 0.3309873 0.6654611 0.4003700 0.4600312 0.6746497 0.4711603 0.5145312
665 666 667 668 669 670 671 672
0.6142318 0.4730765 0.6523223 0.5017336 0.5565380 0.4697832 0.4975482 0.6954920
673 674 675 676 677 678 679 680
0.4981477 0.4522318 0.6600458 0.6050575 0.2832260 0.6341774 0.6092006 0.8271045
681 682 683 684 685 686 687 688
0.3875321 0.4590480 0.7701868 0.5144153 0.6055840 0.5699064 0.6316344 0.6339549
689 690 691 692 693 694 695 696
0.3632363 0.4430689 0.5645229 0.6229264 0.6080875 0.6575720 0.5797677 0.5428814
697 698 699 700 701 702 703 704
0.6059058 0.5456522 0.6877347 0.5539068 0.4255091 0.3314323 0.6123712 0.5258183
705 706 707 708 709 710 711 712
0.5485294 0.3540187 0.4343883 0.7159345 0.5499973 0.5386473 0.5255142 0.4984409
713 714 715 716 717 718 719 720
0.5243771 0.3364618 0.7052032 0.5920626 0.5790450 0.5744355 0.5029695 0.3840295
721 722 723 724 725 726 727 728
0.5839930 0.6044318 0.6559484 0.5553156 0.2051587 0.2242671 0.4266476 0.6935754
729 730 731 732 733 734 735 736
0.6829475 0.6041711 0.6661603 0.4977747 0.3666543 0.6969443 0.6487802 0.5168696
737 738 739 740 741 742 743 744
0.5751670 0.6042553 0.6592254 0.6510552 0.4942161 0.5934895 0.4536989 0.3793843
745 746 747 748 749 750 751 752
0.5039410 0.5519400 0.4376660 0.5422957 0.6312674 0.5078106 0.7051200 0.3210352
753
0.4845593
3 4 5 6 7 8 9
3.915693 3.684508 5.071565 4.774115 5.643041 4.369198 4.130052
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