1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
593
594
595
596
597
598
599
600
601
602
603
604
605
606
607
608
609
610
611
612
613
614
615
616
617
618
619
620
621
622
623
624
625
626
627
628
629
630
631
632
633
634
635
636
637
638
639
640
641
642
643
644
645
646
647
648
649
650
651
652
653
654
655
656
657
658
659
660
661
662
663
664
665
666
667
668
669
670
671
672
673
674
675
676
677
678
679
680
681
682
683
684
685
686
687
688
689
690
691
692
693
694
695
696
697
698
699
700
701
702
703
704
705
706
707
708
709
710
711
712
713
714
715
716
717
718
719
720
721
722
723
724
725
726
727
728
729
730
731
732
733
734
735
736
737
738
739
740
741
742
743
744
745
746
747
748
749
750
751
752
753
754
755
756
757
758
759
760
761
762
763
764
765
766
767
768
769
770
771
772
773
774
775
776
777
778
779
780
781
782
783
784
785
786
787
788
789
790
791
792
793
794
795
796
797
798
799
800
801
802
803
804
805
806
807
808
809
810
811
812
813
814
815
816
817
818
819
820
821
822
823
824
825
826
827
828
829
830
831
832
833
834
835
836
837
838
839
840
841
842
843
844
845
846
847
848
849
850
851
852
853
854
855
856
857
858
859
860
861
862
863
864
865
866
867
868
869
870
871
872
873
874
875
876
877
878
879
880
881
882
883
884
885
886
887
888
889
890
891
892
893
894
895
896
897
898
899
900
901
902
903
904
905
906
907
908
909
910
911
912
913
914
915
916
917
918
919
920
921
922
923
924
925
926
927
928
929
930
931
932
933
934
935
936
937
938
939
940
941
942
943
944
945
946
947
948
949
950
951
952
953
954
955
956
957
958
959
960
961
|
RANDLIB
Library of Fortran Routines for Random Number Generation
Full Documentation of Each Routine
Compiled and Written by:
Barry W. Brown
James Lovato
Department of Biomathematics, Box 237
The University of Texas, M.D. Anderson Cancer Center
1515 Holcombe Boulevard
Houston, TX 77030
This work was supported by grant CA-16672 from the National Cancer Institute.
C**********************************************************************
C
C SUBROUTINE ADVNST(K)
C ADV-a-N-ce ST-ate
C
C Advances the state of the current generator by 2^K values and
C resets the initial seed to that value.
C
C This is a transcription from Pascal to Fortran of routine
C Advance_State from the paper
C
C L'Ecuyer, P. and Cote, S. "Implementing a Random Number Package
C with Splitting Facilities." ACM Transactions on Mathematical
C Software, 17:98-111 (1991)
C
C
C Arguments
C
C
C K -> The generator is advanced by2^K values
C INTEGER K
C
C**********************************************************************
C**********************************************************************
C
C REAL FUNCTION GENBET( A, B )
C GeNerate BETa random deviate
C
C
C Function
C
C
C Returns a single random deviate from the beta distribution with
C parameters A and B. The density of the beta is
C x^(a-1) * (1-x)^(b-1) / B(a,b) for 0 < x < 1
C
C
C Arguments
C
C
C A --> First parameter of the beta distribution
C REAL A
C (A >= 1.0E-37)
C
C B --> Second parameter of the beta distribution
C REAL B
C (B >= 1.0E-37)
C
C
C Method
C
C
C R. C. H. Cheng
C Generating Beta Variables with Nonintegral Shape Parameters
C Communications of the ACM, 21:317-322 (1978)
C (Algorithms BB and BC)
C
C**********************************************************************
C**********************************************************************
C
C REAL FUNCTION GENCHI( DF )
C Generate random value of CHIsquare variable
C
C
C Function
C
C
C Generates random deviate from the distribution of a chisquare
C with DF degrees of freedom random variable.
C
C
C Arguments
C
C
C DF --> Degrees of freedom of the chisquare
C (Must be positive)
C REAL DF
C
C
C Method
C
C
C Uses relation between chisquare and gamma.
C
C**********************************************************************
C**********************************************************************
C
C REAL FUNCTION GENEXP( AV )
C
C GENerate EXPonential random deviate
C
C
C Function
C
C
C Generates a single random deviate from an exponential
C distribution with mean AV.
C
C
C Arguments
C
C
C AV --> The mean of the exponential distribution from which
C a random deviate is to be generated.
C REAL AV
C (AV >= 0)
C
C GENEXP <-- The random deviate.
C REAL GENEXP
C
C
C Method
C
C
C Renames SEXPO from TOMS as slightly modified by BWB to use RANF
C instead of SUNIF.
C
C For details see:
C
C Ahrens, J.H. and Dieter, U.
C Computer Methods for Sampling From the
C Exponential and Normal Distributions.
C Comm. ACM, 15,10 (Oct. 1972), 873 - 882.
C
C**********************************************************************
C**********************************************************************
C
C REAL FUNCTION GENF( DFN, DFD )
C GENerate random deviate from the F distribution
C
C
C Function
C
C
C Generates a random deviate from the F (variance ratio)
C distribution with DFN degrees of freedom in the numerator
C and DFD degrees of freedom in the denominator.
C
C
C Arguments
C
C
C DFN --> Numerator degrees of freedom
C (Must be positive)
C REAL DFN
C DFD --> Denominator degrees of freedom
C (Must be positive)
C REAL DFD
C
C
C Method
C
C
C Directly generates ratio of chisquare variates
C
C**********************************************************************
C**********************************************************************
C
C REAL FUNCTION GENGAM( A, R )
C GENerates random deviates from GAMma distribution
C
C
C Function
C
C
C Generates random deviates from the gamma distribution whose
C density is
C (A**R)/Gamma(R) * X**(R-1) * Exp(-A*X)
C
C
C Arguments
C
C
C A --> Location parameter of Gamma distribution
C REAL A ( A > 0 )
C
C R --> Shape parameter of Gamma distribution
C REAL R ( R > 0 )
C
C
C Method
C
C
C Renames SGAMMA from TOMS as slightly modified by BWB to use RANF
C instead of SUNIF.
C
C For details see:
C (Case R >= 1.0)
C Ahrens, J.H. and Dieter, U.
C Generating Gamma Variates by a
C Modified Rejection Technique.
C Comm. ACM, 25,1 (Jan. 1982), 47 - 54.
C Algorithm GD
C
C (Case 0.0 < R < 1.0)
C Ahrens, J.H. and Dieter, U.
C Computer Methods for Sampling from Gamma,
C Beta, Poisson and Binomial Distributions.
C Computing, 12 (1974), 223-246/
C Adapted algorithm GS.
C
C**********************************************************************
C**********************************************************************
C
C SUBROUTINE GENMN(PARM,X,WORK)
C GENerate Multivariate Normal random deviate
C
C
C Arguments
C
C
C PARM --> Parameters needed to generate multivariate normal
C deviates (MEANV and Cholesky decomposition of
C COVM). Set by a previous call to SETGMN.
C
C 1 : 1 - size of deviate, P
C 2 : P + 1 - mean vector
C P+2 : P*(P+3)/2 + 1 - upper half of cholesky
C decomposition of cov matrix
C REAL PARM(*)
C
C X <-- Vector deviate generated.
C REAL X(P)
C
C WORK <--> Scratch array
C REAL WORK(P)
C
C
C Method
C
C
C 1) Generate P independent standard normal deviates - Ei ~ N(0,1)
C
C 2) SETGMN uses Cholesky decomposition find A s.t. trans(A)*A = COV
C
C 3) Generate trans(A)*E + MEANV ~ N(MEANV,COVM)
C
C**********************************************************************
C**********************************************************************
C
C SUBROUTINE GENMUL( N, P, NCAT, IX )
C GENerate an observation from the MULtinomial distribution
C
C
C Arguments
C
C
C N --> Number of events that will be classified into one of
C the categories 1..NCAT
C INTEGER N
C (N >= 0)
C
C P --> Vector of probabilities. P(i) is the probability that
C an event will be classified into category i. Thus, P(i)
C must be [0,1]. Only the first NCAT-1 P(i) must be defined
C since P(NCAT) is 1.0 minus the sum of the first
C NCAT-1 P(i).
C REAL P(NCAT-1)
C
C NCAT --> Number of categories. Length of P and IX.
C INTEGER NCAT
C (NCAT > 1)
C
C IX <-- Observation from multinomial distribution. All IX(i)
C will be nonnegative and their sum will be N.
C INTEGER IX(NCAT)
C
C
C Method
C
C
C Algorithm from page 559 of
C
C Devroye, Luc
C
C Non-Uniform Random Variate Generation. Springer-Verlag,
C New York, 1986.
C
C**********************************************************************
C**********************************************************************
C
C REAL FUNCTION GENNCH( DF, XNONC )
C Generate random value of Noncentral CHIsquare variable
C
C
C Function
C
C
C
C Generates random deviate from the distribution of a noncentral
C chisquare with DF degrees of freedom and noncentrality parameter
C XNONC.
C
C
C Arguments
C
C
C DF --> Degrees of freedom of the chisquare
C (Must be >= 1.0)
C REAL DF
C
C XNONC --> Noncentrality parameter of the chisquare
C (Must be >= 0.0)
C REAL XNONC
C
C
C Method
C
C
C Uses fact that noncentral chisquare is the sum of a chisquare
C deviate with DF-1 degrees of freedom plus the square of a normal
C deviate with mean XNONC and standard deviation 1.
C
C**********************************************************************
C**********************************************************************
C
C REAL FUNCTION GENNF( DFN, DFD, XNONC )
C GENerate random deviate from the Noncentral F distribution
C
C
C Function
C
C
C Generates a random deviate from the noncentral F (variance ratio)
C distribution with DFN degrees of freedom in the numerator, and DFD
C degrees of freedom in the denominator, and noncentrality parameter
C XNONC.
C
C
C Arguments
C
C
C DFN --> Numerator degrees of freedom
C (Must be >= 1.0)
C REAL DFN
C DFD --> Denominator degrees of freedom
C (Must be positive)
C REAL DFD
C
C XNONC --> Noncentrality parameter
C (Must be nonnegative)
C REAL XNONC
C
C
C Method
C
C
C Directly generates ratio of noncentral numerator chisquare variate
C to central denominator chisquare variate.
C
C**********************************************************************
C**********************************************************************
C
C REAL FUNCTION GENNOR( AV, SD )
C
C GENerate random deviate from a NORmal distribution
C
C
C Function
C
C
C Generates a single random deviate from a normal distribution
C with mean, AV, and standard deviation, SD.
C
C
C Arguments
C
C
C AV --> Mean of the normal distribution.
C REAL AV
C
C SD --> Standard deviation of the normal distribution.
C REAL SD
C (SD >= 0)
C
C GENNOR <-- Generated normal deviate.
C REAL GENNOR
C
C
C Method
C
C
C Renames SNORM from TOMS as slightly modified by BWB to use RANF
C instead of SUNIF.
C
C For details see:
C Ahrens, J.H. and Dieter, U.
C Extensions of Forsythe's Method for Random
C Sampling from the Normal Distribution.
C Math. Comput., 27,124 (Oct. 1973), 927 - 937.
C
C
C**********************************************************************
C**********************************************************************
C
C SUBROUTINE GENPRM( IARRAY, LARRAY )
C GENerate random PeRMutation of iarray
C
C
C Arguments
C
C
C IARRAY <--> On output IARRAY is a random permutation of its
C value on input
C INTEGER IARRAY( LARRAY )
C
C LARRAY <--> Length of IARRAY
C INTEGER LARRAY
C
C**********************************************************************
C**********************************************************************
C
C REAL FUNCTION GENUNF( LOW, HIGH )
C
C GeNerate Uniform Real between LOW and HIGH
C
C
C Function
C
C
C Generates a real uniformly distributed between LOW and HIGH.
C
C
C Arguments
C
C
C LOW --> Low bound (exclusive) on real value to be generated
C REAL LOW
C
C HIGH --> High bound (exclusive) on real value to be generated
C REAL HIGH
C
C**********************************************************************
C**********************************************************************
C
C SUBROUTINE GETCGN(G)
C Get GeNerator
C
C Returns in G the number of the current random number generator
C
C
C Arguments
C
C
C G <-- Number of the current random number generator (1..32)
C INTEGER G
C
C**********************************************************************
C**********************************************************************
C
C SUBROUTINE GETSD(ISEED1,ISEED2)
C GET SeeD
C
C Returns the value of two integer seeds of the current generator
C
C This is a transcription from Pascal to Fortran of routine
C Get_State from the paper
C
C L'Ecuyer, P. and Cote, S. "Implementing a Random Number Package
C with Splitting Facilities." ACM Transactions on Mathematical
C Software, 17:98-111 (1991)
C
C
C Arguments
C
C
C
C ISEED1 <- First integer seed of generator G
C INTEGER ISEED1
C
C ISEED2 <- Second integer seed of generator G
C INTEGER ISEED1
C
C**********************************************************************
C**********************************************************************
C
C INTEGER FUNCTION IGNBIN( N, P )
C
C GENerate BINomial random deviate
C
C
C Function
C
C
C Generates a single random deviate from a binomial
C distribution whose number of trials is N and whose
C probability of an event in each trial is P.
C
C
C Arguments
C
C
C N --> The number of trials in the binomial distribution
C from which a random deviate is to be generated.
C INTEGER N
C (N >= 0)
C
C P --> The probability of an event in each trial of the
C binomial distribution from which a random deviate
C is to be generated.
C REAL P
C (0.0 <= P <= 1.0)
C
C IGNBIN <-- A random deviate yielding the number of events
C from N independent trials, each of which has
C a probability of event P.
C INTEGER IGNBIN
C
C
C Note
C
C
C Uses RANF so the value of the seeds, ISEED1 and ISEED2 must be set
C by a call similar to the following
C DUM = RANSET( ISEED1, ISEED2 )
C
C
C Method
C
C
C This is algorithm BTPE from:
C
C Kachitvichyanukul, V. and Schmeiser, B. W.
C
C Binomial Random Variate Generation.
C Communications of the ACM, 31, 2
C (February, 1988) 216.
C
C**********************************************************************
C**********************************************************************
C
C INTEGER FUNCTION IGNNBN( N, P )
C
C GENerate Negative BiNomial random deviate
C
C
C Function
C
C
C Generates a single random deviate from a negative binomial
C distribution.
C
C
C Arguments
C
C
C N --> Required number of events.
C INTEGER N
C (N > 0)
C
C P --> The probability of an event during a Bernoulli trial.
C REAL P
C (0.0 < P < 1.0)
C
C
C
C Method
C
C
C Algorithm from page 480 of
C
C Devroye, Luc
C
C Non-Uniform Random Variate Generation. Springer-Verlag,
C New York, 1986.
C
C**********************************************************************
C**********************************************************************
C
C INTEGER FUNCTION IGNLGI()
C GeNerate LarGe Integer
C
C Returns a random integer following a uniform distribution over
C (1, 2147483562) using the current generator.
C
C This is a transcription from Pascal to Fortran of routine
C Random from the paper
C
C L'Ecuyer, P. and Cote, S. "Implementing a Random Number Package
C with Splitting Facilities." ACM Transactions on Mathematical
C Software, 17:98-111 (1991)
C
C**********************************************************************
C**********************************************************************
C
C INTEGER FUNCTION IGNPOI( MU )
C
C GENerate POIsson random deviate
C
C
C Function
C
C
C Generates a single random deviate from a Poisson
C distribution with mean MU.
C
C
C Arguments
C
C
C MU --> The mean of the Poisson distribution from which
C a random deviate is to be generated.
C REAL MU
C (MU >= 0.0)
C
C IGNPOI <-- The random deviate.
C REAL IGNPOI (non-negative)
C
C
C Method
C
C
C Renames KPOIS from TOMS as slightly modified by BWB to use RANF
C instead of SUNIF.
C
C For details see:
C
C Ahrens, J.H. and Dieter, U.
C Computer Generation of Poisson Deviates
C From Modified Normal Distributions.
C ACM Trans. Math. Software, 8, 2
C (June 1982),163-179
C
C**********************************************************************
C**********************************************************************
C
C INTEGER FUNCTION IGNUIN( LOW, HIGH )
C
C GeNerate Uniform INteger
C
C
C Function
C
C
C Generates an integer uniformly distributed between LOW and HIGH.
C
C
C Arguments
C
C
C LOW --> Low bound (inclusive) on integer value to be generated
C INTEGER LOW
C
C HIGH --> High bound (inclusive) on integer value to be generated
C INTEGER HIGH
C
C
C Note
C
C
C If (HIGH-LOW) > 2,147,483,561 prints error message on * unit and
C stops the program.
C
C**********************************************************************
C**********************************************************************
C
C SUBROUTINE INITGN(ISDTYP)
C INIT-ialize current G-e-N-erator
C
C Reinitializes the state of the current generator
C ISDTYP = -1 => sets the state to its initial seed
C ISDTYP = 0 => sets the state to its last (previous) seed
C ISDTYP = 1 => sets the state to a new seed 2^w values
C from its last seed
C
C This is a transcription from Pascal to Fortran of routine
C Init_Generator from the paper
C
C L'Ecuyer, P. and Cote, S. "Implementing a Random Number Package
C with Splitting Facilities." ACM Transactions on Mathematical
C Software, 17:98-111 (1991)
C
C
C Arguments
C
C
C ISDTYP -> The state to which the generator is to be set
C
C INTEGER ISDTYP
C
C**********************************************************************
C**********************************************************************
C
C SUBROUTINE INRGCM()
C INitialize Random number Generator CoMmon
C
C
C Function
C
C
C Initializes common area for random number generator. This saves
C the nuisance of a BLOCK DATA routine and the difficulty of
C assuring that the routine is loaded with the other routines.
C
C**********************************************************************
C**********************************************************************
C
C INTEGER FUNCTION MLTMOD(A,S,M)
C
C Returns (A*S) MOD M
C
C This is a transcription from Pascal to Fortran of routine
C MULtMod_Decompos from the paper
C
C L'Ecuyer, P. and Cote, S. "Implementing a Random Number Package
C with Splitting Facilities." ACM Transactions on Mathematical
C Software, 17:98-111 (1991)
C
C
C Arguments
C
C
C A, S, M -->
C INTEGER A,S,M
C
C**********************************************************************
C**********************************************************************
C
C SUBROUTINE PHRTSD( PHRASE, SEED1, SEED2 )
C PHRase To SeeDs
C
C
C Function
C
C
C Uses a phrase (character string) to generate two seeds for the RGN
C random number generator.
C
C
C Arguments
C
C
C PHRASE --> Phrase to be used for random number generation
C CHARACTER*(*) PHRASE
C
C SEED1 <-- First seed for RGN generator
C INTEGER SEED1
C
C SEED2 <-- Second seed for RGN generator
C INTEGER SEED2
C
C
C Note
C
C
C Trailing blanks are eliminated before the seeds are generated.
C
C Generated seed values will fall in the range 1..2^30
C (1..1,073,741,824)
C
C**********************************************************************
C**********************************************************************
C
C REAL FUNCTION RANF()
C RANDom number generator as a Function
C
C Returns a random floating point number from a uniform distribution
C over 0 - 1 (endpoints of this interval are not returned) using the
C current generator
C
C This is a transcription from Pascal to Fortran of routine
C Uniform_01 from the paper
C
C L'Ecuyer, P. and Cote, S. "Implementing a Random Number Package
C with Splitting Facilities." ACM Transactions on Mathematical
C Software, 17:98-111 (1991)
C
C**********************************************************************
C**********************************************************************
C
C SUBROUTINE SETALL(ISEED1,ISEED2)
C SET ALL random number generators
C
C Sets the initial seed of generator 1 to ISEED1 and ISEED2. The
C initial seeds of the other generators are set accordingly, and
C all generators states are set to these seeds.
C
C This is a transcription from Pascal to Fortran of routine
C Set_Initial_Seed from the paper
C
C L'Ecuyer, P. and Cote, S. "Implementing a Random Number Package
C with Splitting Facilities." ACM Transactions on Mathematical
C Software, 17:98-111 (1991)
C
C
C Arguments
C
C
C ISEED1 -> First of two integer seeds
C INTEGER ISEED1
C
C ISEED2 -> Second of two integer seeds
C INTEGER ISEED1
C
C**********************************************************************
C**********************************************************************
C
C SUBROUTINE SETANT(QVALUE)
C SET ANTithetic
C
C Sets whether the current generator produces antithetic values. If
C X is the value normally returned from a uniform [0,1] random
C number generator then 1 - X is the antithetic value. If X is the
C value normally returned from a uniform [0,N] random number
C generator then N - 1 - X is the antithetic value.
C
C All generators are initialized to NOT generate antithetic values.
C
C This is a transcription from Pascal to Fortran of routine
C Set_Antithetic from the paper
C
C L'Ecuyer, P. and Cote, S. "Implementing a Random Number Package
C with Splitting Facilities." ACM Transactions on Mathematical
C Software, 17:98-111 (1991)
C
C
C Arguments
C
C
C QVALUE -> .TRUE. if generator G is to generating antithetic
C values, otherwise .FALSE.
C LOGICAL QVALUE
C
C**********************************************************************
C**********************************************************************
C
C SUBROUTINE SETCGN( G )
C Set GeNerator
C
C Sets the current generator to G. All references to a generato
C are to the current generator.
C
C
C Arguments
C
C
C G --> Number of the current random number generator (1..32)
C INTEGER G
C
C**********************************************************************
C**********************************************************************
C
C SUBROUTINE SETGMN( MEANV, COVM, LDCOVM, P, PARM)
C SET Generate Multivariate Normal random deviate
C
C
C Function
C
C
C Places P, MEANV, and the Cholesky factoriztion of COVM
C in PARM for GENMN.
C
C
C Arguments
C
C
C MEANV --> Mean vector of multivariate normal distribution.
C REAL MEANV(P)
C
C COVM <--> (Input) Covariance matrix of the multivariate
C normal distribution. This routine uses only the
C (1:P,1:P) slice of COVM, but needs to know LDCOVM.
C
C (Output) Destroyed on output
C REAL COVM(LDCOVM,P)
C
C LDCOVM --> Leading actual dimension of COVM.
C INTEGER LDCOVM
C
C P --> Dimension of the normal, or length of MEANV.
C INTEGER P
C
C PARM <-- Array of parameters needed to generate multivariate
C normal deviates (P, MEANV and Cholesky decomposition
C of COVM).
C 1 : 1 - P
C 2 : P + 1 - MEANV
C P+2 : P*(P+3)/2 + 1 - Cholesky decomposition of COVM
C REAL PARM(P*(P+3)/2 + 1)
C
C**********************************************************************
C**********************************************************************
C
C SUBROUTINE SETSD(ISEED1,ISEED2)
C SET S-ee-D of current generator
C
C Resets the initial seed and state of generator g to ISEED1 and
C ISEED2. The seeds and states of the other generators remain
C unchanged.
C
C This is a transcription from Pascal to Fortran of routine
C Set_Seed from the paper
C
C L'Ecuyer, P. and Cote, S. "Implementing a Random Number Package
C with Splitting Facilities." ACM Transactions on Mathematical
C Software, 17:98-111 (1991)
C
C
C Arguments
C
C
C ISEED1 -> First integer seed
C INTEGER ISEED1
C
C ISEED2 -> Second integer seed
C INTEGER ISEED1
C
C**********************************************************************
|
