Untitled
Angelika Anggreni Batubara
2023-02-13
Step1, membangkitkan bil.acak geometrik dengan fungsi inverse transformation method
set.seed(123)
p <- 0.5
data <- -log(runif(1000))/p
data## [1] 2.492525640 0.475740073 1.788193101 0.248820737 0.122756833
## [6] 6.177603957 1.276918455 0.227638952 1.190462563 1.567830547
## [11] 0.088252091 1.582251548 0.778482945 1.115019108 4.547515589
## [16] 0.211110024 2.804134326 6.337338399 2.229966819 0.093127625
## [21] 0.234103145 0.734018010 0.890991039 0.011493408 0.844086135
## [26] 0.689124434 1.217369341 1.041273793 2.481552039 3.833099760
## [31] 0.075353408 0.205618557 0.740084122 0.457650781 7.408905420
## [36] 1.477142953 0.552931654 3.061180121 2.290269703 2.925264408
## [41] 3.892620145 1.761141047 1.765110811 1.994755110 3.761906117
## [46] 3.949355094 2.913140973 1.527300454 2.648723663 0.306703995
## [51] 6.165581848 1.631985685 0.448976796 4.209120627 1.156254197
## [56] 3.154605741 4.118781416 0.566562569 0.221761763 1.964525756
## [61] 0.815590057 4.711114098 1.914383596 2.586455978 0.410017867
## [66] 1.603620325 0.421283173 0.415550725 0.460481551 1.642726307
## [71] 0.563465851 0.926545047 0.684466877 14.756243307 1.487548450
## [76] 3.027174983 1.936133877 0.979527960 2.089396779 4.394011564
## [81] 2.824295618 0.806767788 1.746238457 0.476017399 4.548682577
## [86] 1.665311699 0.030314628 0.226222922 0.241018109 3.485336983
## [91] 4.069767246 0.852044149 2.137040429 0.840878949 2.276537160
## [96] 3.345915300 0.491048530 4.737556915 1.523798555 1.340794039
## [101] 1.021688050 2.200285677 1.432368890 0.093190113 1.455881444
## [106] 0.232280771 0.178890811 0.992744549 1.779834302 3.833357487
## [111] 0.133776312 2.399769676 5.602945466 0.107377712 0.655352504
## [116] 3.899715724 1.198276945 0.093991948 1.070635057 1.810156249
## [121] 0.868057960 2.279990024 2.357129930 3.030369025 1.991269344
## [126] 0.031813278 3.738979794 4.792824748 3.905168031 0.742106779
## [131] 0.958471482 0.229937236 0.792022595 0.610123827 1.303489522
## [136] 0.831520494 0.392503157 0.480880685 0.040768882 1.644546701
## [141] 2.331414055 1.785759087 9.119034288 3.387275321 0.342218930
## [146] 2.929274917 2.861747180 5.135937524 2.807095269 0.623580150
## [151] 0.331039407 1.396209831 1.893968852 2.801200454 4.394712869
## [156] 1.883245617 1.117458763 3.056704456 1.620404953 3.046606042
## [161] 1.377117195 2.077455946 0.861611498 1.963184653 2.068767364
## [166] 1.255887965 0.601306713 3.018253808 1.769845200 2.650875067
## [171] 0.924156466 3.387504143 0.293189006 0.584537138 0.806082148
## [176] 0.962475802 1.976443365 1.270376694 0.267788991 1.083428611
## [181] 0.349259792 2.326633392 0.689802419 2.655916525 1.040596717
## [186] 1.462571389 2.655803891 1.143309410 0.181626522 0.206560053
## [191] 2.588038500 2.269622743 0.028926411 0.956093182 0.129473691
## [196] 1.524854319 1.798706994 0.833364600 3.763193961 1.114203199
## [201] 2.864877432 0.076735566 1.017104001 1.327061314 1.819755964
## [206] 0.255106501 2.020698135 2.487928616 3.536337052 3.518525550
## [211] 1.459445551 2.749008845 3.062595970 0.787933769 6.087173399
## [216] 0.710913979 2.088881043 1.788354113 0.394582920 0.169248788
## [221] 2.527952900 0.079343659 0.633825161 0.752662068 5.880824370
## [226] 1.856624733 1.476936144 1.158732682 0.718322937 0.176168912
## [231] 0.961397308 1.695295469 1.224682019 5.678192618 2.687566925
## [236] 1.846872635 3.241556577 0.368019812 3.756109470 0.437758956
## [241] 1.207248679 0.824020033 3.524030566 0.914394809 2.330339313
## [246] 0.644397015 1.837889378 0.062245843 0.066289806 0.638476095
## [251] 2.715672356 3.012067206 1.044967797 2.637111191 1.265721377
## [256] 0.483400149 3.566858795 1.810705634 1.503348827 0.282881045
## [261] 0.154392953 0.251177333 0.788495984 0.102235084 1.321573374
## [266] 1.101493891 2.179317745 2.114990798 7.821617431 1.375073713
## [271] 0.276126920 10.134162434 5.260592171 3.613203445 0.521861991
## [276] 0.615268110 0.057054859 1.525112948 5.197015026 0.865205683
## [281] 0.552579308 3.974000678 1.849731815 2.983440165 5.696053995
## [286] 1.853224187 5.468943390 2.975445830 5.814376809 0.800113401
## [291] 2.423057339 4.590790359 5.264844062 0.254665701 0.564069691
## [296] 0.405197380 0.036042068 4.534442752 4.624425999 0.449210210
## [301] 0.485225539 9.327738492 0.499319326 0.631091634 0.923652383
## [306] 1.464146821 3.707650403 9.603460502 1.586118933 1.417361087
## [311] 1.885335578 1.532873072 0.675765260 5.789895074 2.072497338
## [316] 0.439268749 0.358950015 2.873076161 2.076995249 0.308902136
## [321] 0.316202407 2.435498156 3.833988015 0.701976399 4.530449753
## [326] 6.778867313 0.001191299 6.711981313 2.167104818 0.177523063
## [331] 0.965010031 2.501532486 0.608172027 0.362913520 2.315000613
## [336] 1.416251410 0.720867524 0.888009562 0.880352515 0.044791026
## [341] 1.760229421 4.250472091 1.284795359 2.982657852 1.441399525
## [346] 1.987343811 0.033579971 1.891855631 2.945929350 0.945462544
## [351] 3.982272447 0.066142770 1.326897910 3.627147407 0.949944561
## [356] 0.028290822 0.804625611 1.740170205 2.258070871 0.360035657
## [361] 3.878426635 3.292038376 0.217981566 2.354534816 2.025049687
## [366] 0.486829056 3.286209881 8.060958699 1.799812063 1.454783088
## [371] 1.726234898 2.141164833 0.286624852 1.574440827 1.255599697
## [376] 0.073653033 0.510838862 3.132025672 2.350208204 0.058152390
## [381] 1.072628453 0.546707430 1.973912533 0.524824362 1.240993861
## [386] 0.179859372 3.371596695 2.530147956 4.708548233 3.116662019
## [391] 0.046334611 2.432750965 0.640457287 0.482391446 4.499648576
## [396] 2.857613659 2.614634615 4.584111561 4.275602160 0.017604138
## [401] 0.028087715 3.974563965 0.198956629 1.102247464 1.855467614
## [406] 1.597893433 0.694858772 4.989847408 2.161667062 0.769009975
## [411] 2.298027237 0.368882969 3.072634373 1.394515490 2.574348912
## [416] 3.300276925 0.101279092 2.268112928 1.474380448 7.151632184
## [421] 1.204933702 0.879367218 1.034145041 2.266796476 0.230565126
## [426] 0.935989066 2.388672667 1.892445189 3.659233071 0.295719922
## [431] 0.096068351 1.146662440 2.220070081 0.006777032 2.897874793
## [436] 0.979851233 4.447944733 1.438848559 4.616284544 3.650643723
## [441] 2.524667146 1.076145846 0.624748436 3.597315482 0.286660748
## [446] 0.689001171 0.547822557 3.833501378 2.054126379 0.791032085
## [451] 1.293204397 2.100777183 2.849815081 5.688021782 2.882601780
## [456] 0.232892554 0.416935006 0.581998277 3.729799671 4.163013929
## [461] 0.051198139 1.659629848 1.535669787 3.600009764 1.072503773
## [466] 2.612911820 2.938509332 0.738629463 2.525660147 0.420459425
## [471] 4.730696098 0.391956603 1.699937538 0.559726083 0.823815113
## [476] 1.621487181 0.933151233 15.345445529 3.053472740 0.699477409
## [481] 3.072686374 0.411752680 2.356844864 0.748681029 0.139383919
## [486] 4.312132670 4.116053952 0.776555745 1.692836381 0.362082407
## [491] 0.057955525 5.304597852 1.553991740 0.708826098 4.885070244
## [496] 0.014161990 2.747949172 6.010012866 0.752808160 0.479238688
## [501] 2.079143530 2.007833077 2.495848473 5.052134595 2.013228250
## [506] 3.451788243 1.247041796 1.370561556 0.113066411 2.149862127
## [511] 1.532667205 4.989158196 0.301397316 1.854396810 0.613323844
## [516] 3.523507483 1.575963769 0.522197756 5.540383248 0.408934354
## [521] 2.400343246 2.017519250 2.328781288 6.573775951 1.312454673
## [526] 0.774228787 0.203548220 7.336060753 0.021963618 2.388786836
## [531] 0.125584838 0.749073958 1.610227851 0.405510282 6.462949830
## [536] 0.604828965 2.106974846 0.374465216 1.248954193 2.585277545
## [541] 0.443917977 4.779672384 0.367586620 2.568522228 0.567087695
## [546] 0.073011458 5.015125299 0.314794146 0.440699373 1.908122251
## [551] 2.231939733 3.170088709 1.126405106 0.237442773 1.270835736
## [556] 1.065601786 0.813726743 1.270162403 1.347305282 8.250372934
## [561] 6.085229150 0.146538255 0.524586133 3.208098752 0.860761377
## [566] 0.850009492 1.856454573 0.415759209 1.206527333 0.244035513
## [571] 1.183659298 0.197325742 1.063889587 1.718575197 0.103459784
## [576] 0.687692587 1.767136945 7.994716987 1.135730150 1.426440800
## [581] 0.258682604 0.414410763 0.315414045 1.999910263 0.269464426
## [586] 3.776476800 2.533032538 0.810814746 0.045752194 1.080029226
## [591] 1.282665742 5.600915774 0.062901122 4.236578829 4.852597085
## [596] 0.253930872 1.353089023 2.172409183 0.223350545 6.885812784
## [601] 2.877452840 0.752326218 2.976048079 2.288299592 3.497585982
## [606] 0.442716333 3.844437234 0.390285051 2.211286927 1.966093351
## [611] 0.924879261 4.673654584 7.633997068 0.013959040 1.075918036
## [616] 0.492253647 0.228811215 0.562431506 0.042031116 6.240457531
## [621] 0.203177753 0.288893928 0.508732927 1.951994336 6.335032753
## [626] 2.018945407 2.591070719 0.323938207 2.030003959 2.378314264
## [631] 0.551150409 0.337228763 1.562114747 0.630430883 4.525217100
## [636] 3.028408401 0.094285424 0.569938069 0.399451347 1.745614476
## [641] 1.042295787 0.449230373 0.236646900 1.908028847 4.808746566
## [646] 0.937629034 0.587034884 4.921322932 2.404497841 0.973690408
## [651] 0.567560567 0.173171009 1.485723420 1.134370598 0.611365307
## [656] 0.307590829 0.190498053 5.751202647 1.374694847 2.096533680
## [661] 0.335521469 0.430263553 4.285508683 0.677427139 2.894052684
## [666] 5.181687965 0.133035844 3.700882189 0.870640697 3.502950803
## [671] 7.816658751 1.302806053 4.900363750 2.524600183 1.732931250
## [676] 1.064513531 0.429620664 3.199022601 1.555560572 1.605285294
## [681] 0.619179926 0.671631435 0.369716794 0.240799140 0.097026800
## [686] 1.193432633 1.298889336 3.535715740 1.470975822 2.742253573
## [691] 6.448749984 0.908888975 1.233999185 3.930746975 2.519592853
## [696] 1.079031230 3.603305790 4.680550853 1.694401304 2.066989063
## [701] 0.336994612 2.693128527 7.531996891 0.296073225 2.189710941
## [706] 0.918400009 1.208711828 1.953969342 3.365383106 1.692873704
## [711] 0.921616557 1.304615744 0.832178680 0.631173130 1.439709864
## [716] 1.911848659 9.971833995 11.207388770 0.010152846 4.453344013
## [721] 1.741348538 0.662893043 0.595359413 0.273934408 0.995595180
## [726] 0.558889912 0.331539479 0.979499742 0.463298828 7.557198435
## [731] 1.749747990 0.267331632 0.869745565 0.157049915 3.517905920
## [736] 2.305211361 0.435674611 0.022195888 2.264014167 13.464869011
## [741] 0.015720382 3.816329620 6.017055690 1.030492485 2.270582981
## [746] 1.277586947 0.457764924 5.349252219 0.727627307 0.105469703
## [751] 2.561928607 2.777341684 3.672231904 5.272481033 1.168809481
## [756] 1.427364982 1.409256222 0.236730343 6.609719470 3.181783780
## [761] 1.331915807 2.884968605 1.105255677 1.458552444 1.126510395
## [766] 3.873769589 3.852290853 1.772089996 0.762490729 0.851046406
## [771] 0.175507669 0.413770050 0.783449872 0.427626654 4.110443727
## [776] 2.766370128 2.207971450 1.796561333 0.907103172 0.424872052
## [781] 2.703390149 0.398201959 8.336714012 0.848070644 0.417200676
## [786] 1.547114562 3.184993440 7.951180830 2.523679193 0.177066613
## [791] 0.137207636 1.223017842 3.033511949 1.429036634 0.443417322
## [796] 1.794787530 4.532283256 2.541898458 2.035173368 2.699964663
## [801] 1.507145852 2.011088478 4.219437750 6.115484286 2.672752111
## [806] 0.063722095 1.432850111 1.477033877 0.578585722 0.808011653
## [811] 6.014978361 0.727384028 2.025264269 0.246294176 0.509017602
## [816] 3.943634745 2.441496990 4.141633121 1.055598991 1.153661608
## [821] 0.745837700 2.334183954 1.003114610 0.018012229 0.593566956
## [826] 5.157807143 1.591826989 5.854766996 2.160235657 0.618622890
## [831] 10.990153878 0.517775973 1.540163532 0.654675190 0.811413123
## [836] 1.116974827 0.702485308 0.839469695 2.480221675 4.661157455
## [841] 0.076605921 0.612142839 0.979683113 4.241712743 1.194732236
## [846] 2.673056754 0.214366950 9.381467957 2.885856956 4.079755693
## [851] 2.240285959 0.639311964 0.016578048 0.670572003 1.368613501
## [856] 1.660007405 0.105061276 4.237504563 5.176666697 0.235267735
## [861] 1.713912260 6.323069469 0.869451686 1.515929722 0.962772740
## [866] 2.612635502 3.699260867 4.338657748 1.355796623 1.202842150
## [871] 3.923015674 3.546632589 0.543655969 1.279611196 0.299346270
## [876] 0.790371283 8.679309524 0.732876612 0.229220252 0.918205955
## [881] 4.464352890 0.164448897 0.785011742 3.813078917 0.587824634
## [886] 0.118228944 1.731274250 2.423182985 2.698562395 3.002231721
## [891] 1.139544176 0.557708617 0.802138928 1.208358525 0.417831354
## [896] 0.551067520 7.817211083 1.930417383 5.956566254 0.451536643
## [901] 0.158737574 1.222771764 0.319481818 1.077206196 0.805965453
## [906] 1.341540459 0.541648366 0.203263203 0.395744865 5.278022872
## [911] 11.095433687 5.905398601 0.286447441 1.102444137 2.317727563
## [916] 0.082757249 1.051222938 1.264445355 1.914555316 2.281662833
## [921] 0.425430592 6.344008406 2.022617088 0.309575509 0.719225429
## [926] 0.758172793 2.111019090 1.178721220 3.971995404 0.484317509
## [931] 0.240130490 3.178330759 0.521112101 1.033811605 0.086504594
## [936] 3.681625526 1.285005952 0.271292701 0.279199949 7.485519068
## [941] 0.048811436 1.425784890 1.887476366 1.746678206 4.751907466
## [946] 3.642674705 1.805680714 2.146974500 1.757713164 2.381109994
## [951] 1.158635322 3.717412649 0.088782204 6.248648895 1.976874950
## [956] 0.076202770 0.875684733 5.585171005 1.783460019 1.707077295
## [961] 1.353925379 1.598794358 0.945578584 3.932541008 0.193139864
## [966] 1.126192213 1.201936254 4.294111485 0.543543085 1.474743888
## [971] 0.491880581 6.157073811 0.397280772 2.623053318 2.525674183
## [976] 0.882532085 0.106550857 9.924131893 2.090421705 1.739550473
## [981] 1.562310266 0.680218463 0.167093555 0.933264396 0.205878502
## [986] 0.555914599 3.963056913 3.751305749 3.307697398 1.673180132
## [991] 4.878659242 2.994183696 1.116712784 1.831735751 1.140212409
## [996] 0.373565678 0.885979404 1.875545904 0.686164476 4.436045418hist(data, main = "Histogram of 1000 Geometric Random Numbers", xlab = "Value", col = "lightblue")
- set.seed(123) digunakan untuk menetapkan seed agar hasil dapat diprediksi (sehingga hasil yang sama akan diperoleh setiap kali program dijalankan).
- runif(1000) membangkitkan 1000 bilangan acak uniform.
- -log(runif(1000))/p adalah transformasi dari bilangan acak uniform ke bilangan acak menyebar geometrik, dimana p adalah parameter sukses.
- Hasil dari transformasi akan disimpan ke dalam objek data.
- Untuk memeriksa distribusi hasil dapat menggunakan histogram seperti diatas
Step2, membangkitkan bil.acak geometrik dengan input nilai p
set.seed(123)
p <- 0.5
data <- rgeom(1000, p)
hist(data, main = "Histogram of 1000 Geometric Random Numbers", xlab = "Value", col = "darkblue")
- set.seed(123) digunakan untuk menetapkan seed agar hasil dapat diprediksi (sehingga hasil yang sama akan diperoleh setiap kali program dijalankan).
- p <- 0.5 menentukan nilai parameter sukses p.
- rgeom(1000, p) membangkitkan 1000 bilangan acak menyebar geometrik dengan parameter sukses p.
- Hasil dari rgeom akan disimpan ke dalam objek data.
- Untuk memeriksa distribusi hasil dapat menggunakan histogram seperti diatas
Membangkitkan bil.acak binomial negatif langsung dari sebaran uniform
set.seed(123)
n <- 10
p <- 0.5
data <- qnbinom(runif(1000), size = n, prob = p)
table(data)## data
## 0 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
## 2 4 13 26 41 69 71 88 97 96 90 74 72 55 53 36 36 15 17 15 9 6 5 6 2 1
## 29
## 1data## [1] 7 13 9 15 18 3 10 16 10 9 19 9 12 10 5 16 7 3 8 18 16 12 11 24
## [25] 11 12 10 11 7 5 19 16 12 13 3 9 13 6 8 7 5 9 9 8 6 5 7 9
## [49] 7 15 3 9 14 5 10 6 5 13 16 8 11 5 8 7 14 9 14 14 13 9 13 11
## [73] 12 0 9 6 8 11 8 5 7 11 9 13 5 9 21 16 16 6 5 11 8 11 8 6
## [97] 13 5 9 10 11 8 9 18 9 16 16 11 9 5 17 7 4 18 12 5 10 18 10 8
## [121] 11 8 7 6 8 21 6 5 5 12 11 16 12 12 10 11 14 13 21 9 7 9 2 6
## [145] 14 7 7 4 7 12 15 9 8 7 5 8 10 6 9 6 10 8 11 8 8 10 13 6
## [169] 9 7 11 6 15 13 12 11 8 10 15 10 14 7 12 7 11 9 7 10 16 16 7 8
## [193] 22 11 17 9 8 11 6 10 7 19 11 10 8 15 8 7 6 6 9 7 6 12 4 12
## [217] 8 9 14 17 7 19 12 12 4 8 9 10 12 17 11 9 10 4 7 8 6 14 6 14
## [241] 10 11 6 11 7 12 8 20 19 12 7 6 11 7 10 13 6 8 9 15 17 15 12 18
## [265] 10 10 8 8 3 10 15 2 4 6 13 12 20 9 4 11 13 5 8 6 4 8 4 6
## [289] 4 12 7 5 4 15 13 14 21 5 5 14 13 2 13 12 11 9 6 2 9 9 8 9
## [313] 12 4 8 14 14 7 8 15 15 7 5 12 5 3 29 3 8 16 11 7 12 14 7 9
## [337] 12 11 11 20 9 5 10 6 9 8 21 8 7 11 5 19 10 6 11 22 12 9 8 14
## [361] 5 6 16 7 8 13 6 2 8 9 9 8 15 9 10 19 13 6 7 20 10 13 8 13
## [385] 10 16 6 7 5 6 20 7 12 13 5 7 7 5 5 23 22 5 16 10 8 9 12 4
## [409] 8 12 8 14 6 9 7 6 18 8 9 3 10 11 11 8 16 11 7 8 6 15 18 10
## [433] 8 25 7 11 5 9 5 6 7 10 12 6 15 12 13 5 8 12 10 8 7 4 7 16
## [457] 14 13 6 5 20 9 9 6 10 7 7 12 7 14 5 14 9 13 11 9 11 0 6 12
## [481] 6 14 7 12 17 5 5 12 9 14 20 4 9 12 4 23 7 4 12 13 8 8 7 4
## [505] 8 6 10 10 18 8 9 4 15 8 12 6 9 13 4 14 7 8 7 3 10 12 16 3
## [529] 22 7 18 12 9 14 3 13 8 14 10 7 14 5 14 7 13 19 4 15 14 8 8 6
## [553] 10 16 10 10 11 10 10 2 4 17 13 6 11 11 8 14 10 15 10 16 10 9 18 12
## [577] 9 2 10 9 15 14 15 8 15 6 7 11 20 10 10 4 19 5 4 15 10 8 16 3
## [601] 7 12 6 8 6 14 5 14 8 8 11 5 3 23 10 13 16 13 21 3 16 15 13 8
## [625] 3 8 7 15 8 7 13 14 9 12 5 6 18 13 14 9 11 14 16 8 5 11 13 4
## [649] 7 11 13 17 9 10 12 15 16 4 10 8 14 14 5 12 7 4 17 6 11 6 3 10
## [673] 4 7 9 10 14 6 9 9 12 12 14 16 18 10 10 6 9 7 3 11 10 5 7 10
## [697] 6 5 9 8 14 7 3 15 8 11 10 8 6 9 11 10 11 12 9 8 2 1 24 5
## [721] 9 12 13 15 11 13 15 11 13 3 9 15 11 17 6 8 14 22 8 1 23 5 4 11
## [745] 8 10 13 4 12 18 7 7 6 4 10 9 9 16 3 6 10 7 10 9 10 5 5 9
## [769] 12 11 17 14 12 14 5 7 8 9 11 14 7 14 2 11 14 9 6 2 7 16 17 10
## [793] 6 9 14 9 5 7 8 7 9 8 5 4 7 19 9 9 13 11 4 12 8 15 13 5
## [817] 7 5 11 10 12 7 11 23 13 4 9 4 8 12 1 13 9 12 11 10 12 11 7 5
## [841] 19 12 11 5 10 7 16 2 7 5 8 12 23 12 10 9 18 5 4 16 9 3 11 9
## [865] 11 7 6 5 10 10 5 6 13 10 15 12 2 12 16 11 5 17 12 5 13 18 9 7
## [889] 7 6 10 13 12 10 14 13 3 8 4 14 17 10 15 10 12 10 13 16 14 4 1 4
## [913] 15 10 7 19 11 10 8 8 14 3 8 15 12 12 8 10 5 13 16 6 13 11 19 6
## [937] 10 15 15 3 20 9 8 9 5 6 8 8 9 7 10 6 19 3 8 19 11 4 9 9
## [961] 10 9 11 5 16 10 10 5 13 9 13 3 14 7 7 11 18 2 8 9 9 12 17 11
## [985] 16 13 5 6 6 9 4 6 10 8 10 14 11 8 12 5barplot(table(data)/n)
hist(table(data))
- set.seed(123) digunakan untuk menetapkan seed agar hasil dapat diprediksi (sehingga hasil yang sama akan diperoleh setiap kali program dijalankan).
- n <- 10 menentukan nilai parameter ukuran (size) n.
- p <- 0.5 menentukan nilai parameter sukses p.
- runif(1000) membangkitkan 1000 bilangan acak uniform.
- qnbinom(runif(1000), size = n, prob = p) mengubah bilangan acak uniform menjadi bilangan acak binomial negatif dengan parameter size = n dan prob = p.