Tue May 20 22:21:57 2025 pdflib_test(): python version: 3.10.12 numpy version: 1.26.4 Test pdflib(). initialize(): rnglib() has been initialized. i4_uni_test(): i4_uni() returns a random positive integer. 695163044 696626468 1059541850 620042603 758075822 330628445 1215929140 1762482382 698994348 730315574 1922376880 722841757 612082173 1081002351 1661144525 45434058 79485022 624052430 184849954 1605430415 r8_uni_01_test(): r8_uni_01 produces a sequence of random values. r8_uni_01() 0.359446 0.208128 0.0797663 0.147932 0.708155 0.395446 0.76442 0.645941 0.473061 0.859549 r8ge_print_test(): r8ge_print() prints an R8GE matrix. Here is an R8MAT: Col: 0 1 2 3 4 Row 0 : 11 12 13 14 15 1 : 21 22 23 24 25 2 : 31 32 33 34 35 3 : 41 42 43 44 45 Col: 5 Row 0 : 16 1 : 26 2 : 36 3 : 46 r8ge_print_some_test(): r8ge_print_some() prints some of an R8GE matrix. Here is an R8GE matrix: Col: 3 4 5 Row 0 : 14 15 16 1 : 24 25 26 2 : 34 35 36 r8mat_norm_fro_affine_test(): r8mat_norm_fro_affine() computes the Frobenius norm of the difference of two R8MAT's; Expected norm = 2.10461 Computed norm = 2.10461 r8po_mv_test(): r8po_mv computes the product of an R8PO matrix and a vector. Matrix order N = 5 Matrix A: Col: 0 1 2 3 4 Row 0 : 2 -1 0 0 0 1 : -1 2 -1 0 0 2 : 0 -1 2 -1 0 3 : 0 0 -1 2 -1 4 : 0 0 0 -1 2 Vector V: 0: 1 1: 2 2: 3 3: 4 4: 5 Product w = A * v: 0: 0 1: 0 2: 0 3: 0 4: 6 r8ut_sl_test(): r8ut_sl solves a linear system A*x=b with R8UT matrix Matrix order N = 5 The upper triangular matrix: Col: 0 1 2 3 4 Row 0 : 1 2 3 4 5 1 : 2 3 4 5 2 : 3 4 5 3 : 4 5 4 : 5 Right hand side b: 0: 55 1: 54 2: 50 3: 41 4: 25 Solution: 0: 1 1: 2 2: 3 3: 4 4: 5 r8vec_indicator1_test(): r8vec_indicator1 returns the 1-based indicator matrix. The 1-based indicator vector: 0: 1 1: 2 2: 3 3: 4 4: 5 5: 6 6: 7 7: 8 8: 9 9: 10 i4_binomial_pdf_test(): i4_binomial_pdf() evaluates the binomial pdf pdf(n,p,k) = probability, in n trials, of k successes, if a single success has probability p. N P K PDF(N,P,K) PDF(N,P,K) tabulated computed 5 0.829509 5 0.392741 0.392741 12 0.0661187 5 0.000619997 0.000619997 6 0.043829 0 0.764211 0.764211 13 0.449539 0 0.000426035 0.000426035 9 0.797287 7 0.302948 0.302948 1 0.350752 1 0.350752 0.350752 2 0.859097 0 0.0198537 0.0198537 17 0.00751236 2 0.00685439 0.00685439 6 0.113664 6 2.15645e-06 2.15645e-06 8 0.267132 7 0.000569115 0.000569115 i4_binomial_sample_test(): i4_binomial_sample() samples the binomial distribution. N P K PDF(N,P,K) 6 0.363595 4 0.106176 20 0.316559 6 0.189202 8 0.21104 3 0.1609 3 0.466774 1 0.398153 18 0.860638 16 0.269221 18 0.607563 10 0.168706 1 0.790208 1 0.790208 7 0.375244 3 0.281742 11 0.695596 6 0.136784 7 0.0910957 0 0.512421 initialize(): rnglib() has been initialized. i4_uniform_sample_test(): i4_uniform_sample() samples the uniform distribution on integers. Generate C between A and B. A B C -3 17 16 -6 9 -4 -4 12 3 4 10 9 -2 19 11 -8 -5 -8 4 14 8 10 12 10 7 20 12 -3 16 10 i4vec_multinomial_pdf_test(): i4vec_multinomial_pdf() evaluates the multinomial PDF. Given M possible outcomes on a single trial, with each outcome having probability P, PDF is the probability that after N trials, outcome I occurred X(I) times. N M I P X PDF() PDF() tabulated computed 0 0.7000 2 1 0.3000 1 3 2 0.441 0.441 0 0.7000 2 1 0.3000 2 4 2 0.2646 0.2646 0 0.5000 2 1 0.5000 1 3 2 0.375 0.375 0 0.6000 1 1 0.0000 1 2 0.4000 1 3 3 0 0 0 0.6000 3 1 0.1000 0 2 0.1000 0 3 0.1000 0 4 0.1000 0 3 5 0.216 0.216 0 0.6000 2 1 0.1000 1 2 0.1000 0 3 0.1000 0 4 0.1000 0 3 5 0.108 0.108 0 0.6000 1 1 0.1000 0 2 0.1000 2 3 0.1000 0 4 0.1000 0 3 5 0.018 0.018 0 0.6000 1 1 0.1000 0 2 0.1000 0 3 0.1000 1 4 0.1000 1 3 5 0.036 0.036 0 0.6000 0 1 0.1000 0 2 0.1000 0 3 0.1000 3 4 0.1000 0 3 5 0.001 0.001 0 0.6000 0 1 0.1000 1 2 0.1000 1 3 0.1000 1 4 0.1000 0 3 5 0.006 0.006 i4vec_multinomial_sample_test(): i4vec_multinomial_sample() samples the multinomial distribution. N M I P X PDF() 0 0.4617 3 1 0.5383 0 3 2 0.0983941 0 0.1045 0 1 0.1992 0 2 0.1558 0 3 0.2001 0 4 0.0765 1 5 0.2370 2 6 0.0224 0 7 0.0045 0 3 8 0.0128945 0 0.2232 0 1 0.1687 0 2 0.0046 0 3 0.0128 0 4 0.0995 2 5 0.2904 0 6 0.2007 0 2 7 0.00990661 0 0.2228 1 1 0.1257 1 2 0.0984 0 3 0.2671 0 4 0.0912 0 5 0.1948 0 2 6 0.0560115 0 0.4380 1 1 0.5620 1 2 2 0.492316 0 0.2436 1 1 0.0182 0 2 0.0220 0 3 0.0147 0 4 0.0764 0 5 0.1024 0 6 0.2263 3 7 0.0965 1 8 0.1278 0 9 0.0721 0 5 10 0.00544816 0 0.2283 2 1 0.1828 1 2 0.2311 2 3 0.2369 0 4 0.1209 0 5 5 0.0152703 0 0.1651 0 1 0.1209 0 2 0.1009 2 3 0.1054 0 4 0.1685 0 5 0.0566 0 6 0.0364 0 7 0.0802 0 8 0.1660 0 2 9 0.0101715 0 0.0482 0 1 0.2405 2 2 0.2616 1 3 0.0203 0 4 0.0607 0 5 0.2876 0 6 0.0811 1 4 7 0.0147201 0 0.6444 1 1 0.3556 2 3 2 0.244495 r8_beta_pdf_test(): r8_beta_pdf() evaluates the BETA PDF. ALPHA BETA X PDF() PDF() tabulated computed 1.09209 4.78159 0.866722 0.00282614 0.00282614 2.80848 2.07654 0.0460776 0.0420895 0.0420895 1.28789 0.549784 0.0221162 0.218406 0.218406 3.16983 0.308636 0.458254 0.133514 0.133514 2.00653 3.77337 0.832083 0.107057 0.107057 0.00919186 4.48752 0.352059 0.00579639 0.00579639 0.472724 0.0680845 0.898529 0.55188 0.55188 4.20424 0.61552 -0.0169242 0 0 1.30151 4.56242 0.0971888 2.87907 2.87907 1.75814 4.11444 0.262167 2.12699 2.12699 r8_beta_sample_test(): r8_beta_sample() samples the beta distribution. ALPHA BETA X PDF() 1.3726 2.05825 0.15366 1.409 2.16488 3.3362 0.164926 1.39948 3.86078 1.14714 0.970088 2.81609 1.6498 2.01847 0.304838 1.41378 1.04698 2.30381 0.189069 1.74627 3.57735 0.40392 0.998826 40.9879 0.91973 0.746162 0.905509 1.2777 0.130492 1.43696 0.101776 0.970987 0.883233 1.12511 0.694178 0.885775 2.8001 2.97079 0.398765 1.75176 r8_chi_pdf_test(): r8_chi_pdf() evaluates the standard chi PDF. DF X PDF() PDF() tabulated computed 1 0.01 3.96953 3.96953 2 0.01 0.497506 0.497506 1 0.02 2.79288 2.79288 2 0.02 0.495025 0.495025 1 0.4 0.516442 0.516442 2 0.4 0.409365 0.409365 3 0.4 0.206577 0.206577 4 0.4 0.0818731 0.0818731 1 1 0.241971 0.241971 2 1 0.303265 0.303265 3 1 0.241971 0.241971 4 1 0.151633 0.151633 5 1 0.0806569 0.0806569 3 2 0.207554 0.207554 3 3 0.15418 0.15418 3 4 0.107982 0.107982 3 5 0.0732249 0.0732249 3 6 0.0486522 0.0486522 10 1 0.000789753 0.000789753 10 2 0.00766416 0.00766416 10 3 0.0235333 0.0235333 r8_chi_sample_test(): r8_chi_sample() samples the CHI distribution: DF R PDF 10.5733 12.4558 0.0672532 1.1536 3.14607 0.0554173 9.91121 11.3392 0.0734821 13.5937 7.18262 0.0461856 6.67546 11.0441 0.0388907 14.9157 14.0943 0.0755482 8.06463 4.87997 0.104264 19.9008 7.92338 0.00658252 5.25517 4.99098 0.125112 9.73528 8.46786 0.0976633 r8_exponential_01_pdf_test(): r8_exponential_01_pdf() evaluates the standard exponential pdf. X PDF() PDF() tabulated computed 0.701301 0.49594 0.49594 4.75975 0.00856778 0.00856778 4.0623 0.0172094 0.0172094 2.58932 0.0750707 0.0750707 1.78419 0.167933 0.167933 -0.136347 0 0 0.916678 0.399845 0.399845 0.104762 0.900538 0.900538 -0.258941 0 0 2.98681 0.050448 0.050448 r8_exponential_01_sample_test(): r8_exponential_01_sample() samples the standard exponential PDF: R PDF(R) 0.78836 0.45459 0.0733068 0.929316 0.348489 0.705753 1.58665 0.20461 0.228993 0.795334 0.116967 0.889615 2.00871 0.134161 0.0938675 0.910403 0.213049 0.808116 0.0169809 0.983162 r8_exponential_pdf_test(): r8_exponential_pdf() evaluates the exponential PDF. BETA X PDF() PDF() tabulated computed 1.09209 9.55881 0.0001447 0.0001447 4.14755 5.57312 0.0628985 0.0628985 2.07654 0.567799 0.366361 0.366361 1.28789 1.01056 0.354279 0.354279 0.219145 6.30305 1.47258e-12 1.47258e-12 0.308636 4.44034 1.82964e-06 1.82964e-06 2.00653 7.5222 0.011734 0.011734 3.98643 -0.0814325 0 0 4.48752 3.4426 0.103472 0.103472 0.472724 0.0375306 1.95395 1.95395 r8_exponential_sample_test(): r8_exponential_sample() samples the general exponential PDF: BETA R PDF 7.43399 1.47739 0.110273 1.74786 0.425896 0.448404 6.016 6.81483 0.0535464 9.48835 5.37419 0.0598171 1.00002 0.552428 0.575544 0.791637 0.0820784 1.13879 9.32772 2.54749 0.0815857 6.51345 11.4192 0.0265949 9.0242 9.14952 0.0402037 3.29655 1.61712 0.185737 r8_gamma_01_pdf_test(): r8_gamma_01_pdf() evaluates the standard gamma PDF. ALPHA X PDF(0,1) PDF(0,1) tabulated computed 1.09209 9.54133 9.26081e-05 9.26081e-05 4.14755 5.3978 0.126034 0.126034 2.07654 0.194247 0.136354 0.136354 1.28789 0.654546 0.511445 0.511445 0.219145 6.15664 0.000123014 0.000123014 0.308636 4.22016 0.00187034 0.00187034 2.00653 7.42407 0.004476 0.004476 3.98643 -0.480697 0 0 4.48752 3.1829 0.205667 0.205667 0.472724 -0.357023 0 0 r8_gamma_01_sample_test(): r8_gamma_01_sample() samples the standard gamma distribution. A X PDF() 3.539 6.20764 0.0598313 2.9115 4.2922 0.119963 1.48948 0.570392 0.484766 4.72864 3.62411 0.201745 3.27177 3.43262 0.204167 0.428545 1.88886 0.0508589 4.60358 1.56538 0.0781258 1.03572 0.528376 0.587678 2.63138 5.15785 0.0571115 2.2039 0.324836 0.169041 r8_gamma_pdf_test(): r8_gamma_pdf() evaluates a gamma PDF. BETA ALPHA X PDF PDF tabulated computed 1.09209 4.78159 4.94296 0.167202 0.167202 2.80848 2.07654 0.209936 0.852212 0.852212 1.28789 0.549784 0.0717398 2.12227 2.12227 3.16983 0.308636 2.58714 6.99377e-05 6.99377e-05 2.00653 3.77337 4.74318 0.0167938 0.0167938 0.00919186 4.48752 1.97466 6.68746e-10 6.68746e-10 0.472724 0.0680845 5.1264 0.00129544 0.00129544 4.20424 0.61552 -0.153423 0 0 1.30151 4.56242 0.504717 0.0118989 0.0118989 1.75814 4.11444 1.45622 0.365884 0.365884 r8_gamma_sample_test(): r8_gamma_sample() samples a gamma distribution. R A X PDF() 0.481256 3.84788 13.5052 0.030065 2.67771 0.967089 0.141969 1.85288 0.484927 4.4082 11.9685 0.0571818 0.659287 1.8472 2.49151 0.205576 0.731147 0.923104 0.486103 0.528112 3.74203 2.71406 0.389513 1.06375 4.86945 0.738903 0.165517 1.85491 0.695694 1.73792 1.65854 0.266134 4.78827 1.48997 0.0407941 1.99729 2.57935 4.21157 0.937002 0.497103 r8_invchi_pdf_test: r8_invchi_pdf returns values of the inverse Chi Square Probability Density Function. DF X PDF PDF 1 0.1 0.08500366602520341 0.08500366602520341 2 0.1 0.3368973499542734 0.3368973499542732 1 0.2 0.3661245640481622 0.3661245640481621 2 0.2 1.026062482798735 1.026062482798735 1 0.4 0.4518059816704532 0.4518059816704532 2 0.4 0.8953274901880941 0.8953274901880941 3 0.4 1.129514954176133 1.129514954176133 4 0.4 1.119159362735118 1.119159362735117 1 1 0.2419707245191433 0.2419707245191434 2 1 0.3032653298563167 0.3032653298563167 3 1 0.2419707245191433 0.2419707245191434 4 1 0.1516326649281584 0.1516326649281584 5 1 0.08065690817304778 0.08065690817304777 3 2 0.0549239111834653 0.05492391118346532 3 3 0.02166329508030457 0.02166329508030457 3 4 0.01100204146138436 0.01100204146138436 3 5 0.006457369034861447 0.006457369034861448 3 6 0.004162370481945731 0.004162370481945732 10 1 0.0007897534631674914 0.0007897534631674914 10 2 1.584474249412852e-05 1.584474249412853e-05 10 3 1.511920090468204e-06 1.511920090468204e-06 r8_invchi_sample_test(): r8_invchi_sample() samples an inverse chi square distribution. DF X PDF() 4.92973 0.14308 3.57359 1.09282 0.288599 0.508755 1.10178 1.06616 0.23963 1.93526 1.01015 0.299657 1.92011 1.1361 0.251563 1.82689 0.923776 0.339902 2.58933 0.477108 0.869327 3.3107 0.767578 0.370797 4.66487 0.178333 3.16154 4.46646 0.73085 0.263508 r8_invgam_pdf_test: r8_invgam_pdf evaluates the inverse gamma Probability Density Function. ALPHA BETA X PDF PDF 1 0.5 1 0.3032653298563167 0.3032653298563167 1 0.5 2 0.09735009788392561 0.09735009788392562 1 0.5 3 0.047026762493923 0.047026762493923 1 0.5 4 0.02757802820576861 0.02757802820576861 1 2 2 0.1839397205857212 0.1839397205857211 1 3 2 0.1673476201113224 0.1673476201113224 1 4 2 0.1353352832366127 0.1353352832366127 1 5 2 0.1026062482798735 0.1026062482798735 2 2 3 0.07606179541223586 0.07606179541223584 3 2 3 0.02535393180407862 0.02535393180407861 4 2 3 0.005634207067573026 0.005634207067573021 5 2 3 0.0009390345112621711 0.0009390345112621706 r8_invgam_sample_test(): r8_invgam_sample() samples an inverse gamma distribution. R A X PDF() 2.40449 3.56069 0.706838 1.03665 3.09224 1.6496 0.361384 0.0203977 4.55011 0.712416 117.262 0.000633673 1.80742 1.08429 0.612387 0.288086 3.18968 4.27745 0.673188 1.17452 4.20455 0.936674 9.43778 0.0305763 0.575913 2.56878 0.216253 2.85796 0.0917012 0.783623 0.0428084 4.21092 1.78035 4.06268 0.41768 1.87722 4.79777 4.80497 1.45786 0.434773 r8_normal_01_pdf_test: r8_normal_01_pdf evaluates the standard normal pdf with mean = 0 and standard deviation = 1. X PDF(0,1) PDF(0,1) tabulated computed -2.252653624140994 0.03155059887555709 0.03155059887555706 3.650540612071437 0.0005094586261557538 0.0005094586261557547 2.636073871461605 0.01235886992552887 0.01235886992552886 0.4935635421351536 0.353192862601275 0.353192862601275 -0.6775433481923101 0.3171212685764107 0.3171212685764107 -3.471050120671749 0.0009653372813755943 0.000965337281375596 -1.939377660943641 0.06083856556197816 0.0608385655619781 -3.120345651740235 0.003066504313116445 0.003066504313116445 -3.649368017767143 0.0005116437388114821 0.0005116437388114826 1.0717256984193 0.2246444116615346 0.2246444116615346 r8_normal_01_sample_test(): r8_normal_01_sample() samples the normal distribution. X PDF(X) 1.48171 0.133097 0.512835 0.349784 -0.425522 0.364411 -2.24624 0.0320091 -0.628343 0.327474 -2.25806 0.0311683 0.230718 0.388464 0.0899485 0.397332 0.504381 0.351292 -0.092292 0.397247 r8_normal_pdf_test: r8_normal_pdf evaluates the normal pdf pdf(mu,sigma) is the normal pdf with mu = mean, sigma = standard deviation. MU SIGMA X PDF(MU,SIGMA) PDF(MU,SIGMA) tabulated computed -56.31634060352484 4.785956124893755 -46.85424018542929 0.01180775937213258 0.01180775937213258 12.33908855337884 2.13500469923221 6.781057314200307 0.006307849174478944 0.006307849174478969 -48.48444152359102 0.6387882883091059 -50.23282168570062 0.0147514774470322 0.0147514774470322 26.7931424604825 0.4024634224214489 26.67129012408019 0.9468437743011001 0.9468437743011002 -19.73874370047668 3.79790008346491 -12.9643468135976 0.02140312299941794 0.0214031229994179 -99.63232576831896 4.497769898408682 -103.6600156181528 0.05939959967353488 0.05939959967353472 -81.09104995766396 0.1667227687589636 -80.73183222587458 0.2348929157422787 0.2348929157422788 68.16949013113364 0.7032091872463158 66.09155915000321 0.007207515678571277 0.007207515678571277 -47.93940044652702 4.57117016420902 -58.53544475210675 0.005944396897656727 0.005944396897656727 -29.67426801922078 4.132147851761006 -35.44773135435396 0.03637663165771322 0.03637663165771318 r8_normal_sample_test(): r8_normal_sample() samples the normal distribution. MU SIGMA X PDF(MU,SIGMA) 78.0065 0.881319 77.3748 0.350118 -75.171 0.500221 -75.4551 0.678792 98.6798 0.599985 99.751 0.135101 22.6471 0.463588 21.7497 0.132192 -84.6463 0.216699 -84.5251 1.57429 81.4526 0.174729 81.3467 1.90022 -88.2205 0.344631 -88.3863 1.0311 60.6239 0.949479 59.7601 0.277793 -82.001 0.580545 -81.8179 0.65384 -14.863 0.960334 -15.8255 0.251388 r8_scinvchi_pdf_test: r8_scinvchi_pdf evaluates the scaled inverse Chi Square Probability Density Function. DF XI X PDF PDF 1 0.5 0.1 0.7322491280963244 0.7322491280963243 2 0.5 0.1 0.3368973499542734 0.3368973499542732 1 0.5 0.2 0.9036119633409063 0.9036119633409061 2 0.5 0.2 1.026062482798735 1.026062482798735 1 0.5 0.4 0.5968580144169457 0.5968580144169456 2 0.5 0.4 0.8953274901880941 0.8953274901880939 1 1 0.1 0.08500366602520341 0.08500366602520341 2 1 0.1 0.004539992976248485 0.004539992976248483 1 1 0.2 0.3661245640481622 0.3661245640481621 2 1 0.2 0.1684486749771367 0.1684486749771366 1 1 0.4 0.4518059816704532 0.4518059816704532 2 1 0.4 0.5130312413993675 0.5130312413993674 1 2 0.1 0.0008099910956089117 0.0008099910956089113 2 2 0.1 4.122307244877116e-07 4.122307244877103e-07 1 2 0.2 0.04250183301260171 0.0425018330126017 2 2 0.2 0.002269996488124243 0.002269996488124244 1 2 0.4 0.1830622820240811 0.1830622820240811 2 2 0.4 0.08422433748856833 0.08422433748856835 r8_scinvchi_sample_test(): r8_scinvchi_sample() samples a scaled inverse chi square distribution. DF XI X PDF 2.78747 2.18275 4.66228 0.0694022 4.20202 0.683536 0.70752 0.784776 4.29747 0.837351 0.788686 0.710661 1.16492 0.879192 1.98941 0.11515 3.36528 4.37436 10.9731 0.0262829 2.71589 2.2921 10.28 0.0159344 4.09261 0.711163 0.874787 0.60136 4.71041 0.496806 0.34675 1.43484 4.95442 2.64706 1.13363 0.160304 2.18717 2.01435 0.292254 0.0173996 r8_uniform_01_pdf_test(): r8_uniform_01_pdf() evaluates the standard uniform PDF. X PDF() 0.5714390922914887 1 0.4052169266429113 1 -0.009065401294131803 0 0.09320922309156976 1 -0.4506747406872307 0 0.02288164963247552 1 0.3781053709093063 1 -0.1064017938749231 0 0.5796290949801046 1 0.3758578009639628 1 r8_uniform_01_sample_test(): r8_uniform_01_sample returns random values in [0,1]: 0.323711 0.324392 0.493388 0.28873 0.353007 0.153961 0.566211 0.82072 0.325495 0.34008 r8_uniform_pdf_test(): r8_uniform_pdf() evaluates the uniform pdf over [A,B]. A B X PDF() 16.6603 22.3404 99.8931 0 -85.4176 85.287 83.2063 0.00585807 -74.5718 92.4791 -88.1952 0 -51.375 -41.3816 33.0842 0 -15.7455 29.8391 -71.1061 0 -63.4837 28.4751 -0.959816 0.0108744 -46.1558 14.4095 -41.1995 0.0165111 -71.0249 49.9246 -35.3769 0.00826791 -98.1642 79.5169 -52.0573 0.00562806 -59.6836 -17.7098 -68.437 0 r8_uniform_sample_test(): r8_uniform_sample() returns random values in [A,B]: A B R -39.8226 -8.28077 -20.4037 -8.64709 1.81528 -8.20692 -52.5643 42.3338 3.7042 58.7596 59.5798 58.7786 33.4339 61.8699 44.8031 -57.3844 -34.0634 -42.8009 -16.3986 33.348 0.0327571 -35.9383 -1.0733 -9.61789 -99.0925 39.4535 -10.1858 -79.9803 -64.7202 -72.2586 initialize(): rnglib() has been initialized. r8vec_multinormal_pdf_test(): r8vec_multinormal_pdf() evaluates the PDF for the multinormal distribution. The covariance matrix is C. The definition uses the inverse of C; r8vec_multinormal_pdf uses the Cholesky factor R Verify that the algorithms are equivalent. R1: Col: 0 1 2 3 4 Row 0 : 0.679714 0.688335 0.138557 0.527999 0.147399 1 : 0.0549453 0.837053 0.0623376 0.297601 2 : 0.0527847 0.782623 0.968703 3 : 0.72663 0.489492 4 : 0.767345 C: Col: 0 1 2 3 4 Row 0 : 0.462011 0.467871 0.0941793 0.358888 0.100189 1 : 0.467871 0.476823 0.141366 0.366865 0.117812 2 : 0.0941793 0.141366 0.722642 0.166648 0.320664 3 : 0.358888 0.366865 0.166648 1.42316 1.21019 4 : 0.100189 0.117812 0.320664 1.21019 1.8771 R2: Col: 0 1 2 3 4 Row 0 : 0.679714 0.688335 0.138557 0.527999 0.147399 1 : 0.0549453 0.837053 0.0623376 0.297601 2 : 0.0527847 0.782623 0.968703 3 : 0.72663 0.489492 4 : 0.767345 Determinant of C = 1.2082e-06 inverse(C): Col: 0 1 2 3 4 Row 0 : 205106 -204994 13529.3 -286.862 -207.726 1 : -204994 204886 -13522.6 285.197 208.498 2 : 13529.3 -13522.6 894.07 -18.5124 -14.2047 3 : -286.862 285.197 -18.5124 2.66467 -1.14406 4 : -207.726 208.498 -14.2047 -1.14406 1.69832 MU: 0: 1.35338 1: -1.62859 2: -0.663114 3: -0.377984 4: 1.04022 X: 0: 1.38262 1: -1.623 2: -0.672352 3: -0.378696 4: 1.02984 PDF1 = 1.9399824444201218e-23 PDF2 = 1.9399824444201077e-23 initialize(): rnglib() has been initialized. r8vec_multinormal_sample_test(): r8vec_multinormal_sample() samples the multinormal distribution. N I MU X PDF() 0 -4.4635 -5.5490 1 -3.5374 -2.6147 2 4.5121 2.7038 3 0.9345 1.8589 4 2.2717 2.1662 5 0.00111289 0 4.3597 3.3490 1 1.4867 0.0198 2 2.4781 3.9424 3 1.3852 1.2487 4 -1.2670 -1.8823 5 0.000732423 0 4.8049 4.9224 1 4.5097 0.6921 2 3.8846 4.9797 3 -2.9952 -4.0536 4 -3.4601 -2.1621 5 2.74154e-06 0 3.1784 2.8220 1 1.2625 2.1762 2 -0.7978 0.3747 3 4.1616 3.0093 4 3.2807 3.5389 5 0.00112528 0 2.2572 1.3256 1 -1.9752 -3.5283 2 -4.4704 -5.5647 3 -3.2103 -1.7302 4 4.6097 5.4575 5 7.61649e-05 0 -1.9894 -2.2762 1 0.2340 0.0488 2 -0.1390 -0.9470 3 1.6377 1.6652 4 3.7748 4.0484 5 0.00201667 0 1.6370 -0.1519 1 -1.3683 1.0815 2 -2.5405 -5.5372 3 -2.9483 -2.9720 4 0.2605 3.6617 5 1.05654e-05 0 -0.4386 -0.9170 1 -2.9277 -2.6285 2 -4.1112 -4.5324 3 -0.4180 -0.3605 4 -4.9666 -4.0975 5 0.00296556 0 -1.6482 -2.3410 1 -3.1109 -4.0181 2 -1.4802 -1.8346 3 -4.9326 -3.5785 4 -2.0228 -1.8057 5 0.00101385 0 -3.1668 -4.2347 1 -4.6414 -5.2897 2 -1.3217 -0.6563 3 -1.9474 -2.3346 4 -1.1271 0.5483 5 0.000880895 pdflib_test(): Normal end of execution. Tue May 20 22:21:58 2025