Draw samples from a posterior object using
rejection sampling
posterior_samples(posterior_obj, n, lower, upper)A vector of samples from the posterior distribution
# define a likelihood
data_model <- likelihood(family = "binomial", 10, 20)
# define a prior
prior_model <- prior(family = "beta", 10, 10)
# compute a posterior
post <- extract_posterior(data_model * prior_model)
# Draw 1000 samples from the posterior
posterior_samples(post, n = 1000, lower = 0, upper = 1)
#> [1] 0.4023282 0.4035381 0.4790245 0.4611865 0.4936370 0.5700450 0.5962628
#> [8] 0.5446034 0.4467025 0.3900314 0.5279170 0.4800752 0.4007202 0.6717668
#> [15] 0.5185566 0.4039110 0.5076503 0.5117913 0.5523776 0.6118524 0.5935538
#> [22] 0.4562302 0.5683527 0.6642855 0.4848028 0.4172699 0.5984750 0.5428372
#> [29] 0.5088936 0.5761874 0.5325652 0.5268303 0.4353866 0.2884170 0.3607776
#> [36] 0.3786412 0.4590177 0.3799467 0.4387573 0.3456832 0.5529002 0.4717556
#> [43] 0.3927519 0.5261067 0.5299348 0.4698789 0.5160349 0.5494615 0.5938366
#> [50] 0.5283224 0.5012471 0.5512907 0.4958896 0.4159615 0.4591390 0.5242801
#> [57] 0.5447052 0.5031461 0.3505882 0.5168041 0.5787815 0.6345443 0.5287093
#> [64] 0.5437927 0.4558401 0.4680893 0.4421869 0.4581606 0.6572984 0.4469974
#> [71] 0.4607475 0.5138669 0.6502987 0.5083099 0.5030267 0.5033951 0.4194859
#> [78] 0.4958347 0.4294316 0.5304095 0.3734108 0.5014234 0.4124729 0.3959981
#> [85] 0.4513363 0.3966740 0.7044640 0.5257314 0.3954480 0.5784610 0.4841195
#> [92] 0.4376551 0.4213711 0.4245976 0.5228954 0.4665975 0.4142487 0.5420758
#> [99] 0.4402233 0.4814845 0.5662714 0.4455378 0.4785984 0.4565847 0.5745623
#> [106] 0.6619993 0.4516670 0.4852220 0.4308361 0.6137436 0.4329577 0.5052717
#> [113] 0.4356070 0.5416781 0.4481785 0.3576113 0.5611449 0.6602534 0.4800047
#> [120] 0.4069197 0.4466452 0.5194664 0.5113113 0.4980553 0.5424417 0.6727037
#> [127] 0.4919785 0.4919778 0.4565150 0.4260052 0.4814955 0.5453928 0.5254825
#> [134] 0.5511978 0.5801826 0.4793860 0.4353852 0.4513757 0.6006700 0.6706232
#> [141] 0.6309976 0.4134435 0.5123930 0.5150504 0.5135930 0.4176636 0.4344885
#> [148] 0.3473396 0.4845777 0.5292034 0.4290002 0.5655163 0.5750370 0.5982999
#> [155] 0.5207486 0.4408169 0.4893102 0.5034499 0.5361411 0.5070840 0.4657682
#> [162] 0.4136132 0.5226437 0.4591184 0.5359932 0.4843596 0.6493836 0.5095380
#> [169] 0.5971393 0.4889994 0.5617880 0.5232697 0.6451981 0.5644536 0.4536133
#> [176] 0.4719390 0.4145562 0.5413156 0.3810109 0.4274280 0.3561430 0.4221801
#> [183] 0.6042523 0.4041968 0.4739241 0.3192830 0.4185217 0.5440445 0.6080354
#> [190] 0.4762322 0.4405450 0.3992167 0.5755505 0.4616787 0.6627989 0.4749383
#> [197] 0.4680662 0.4871230 0.5135570 0.4350371 0.4423943 0.3727998 0.4314967
#> [204] 0.4623544 0.5196348 0.5850109 0.4680848 0.4155690 0.4497093 0.3804787
#> [211] 0.4464889 0.3924567 0.5115403 0.3642891 0.4839433 0.3686010 0.5234972
#> [218] 0.4079209 0.4341059 0.4213487 0.4799975 0.4772812 0.4912678 0.5356092
#> [225] 0.5284277 0.6009530 0.4214927 0.5282096 0.5090210 0.4914389 0.4903440
#> [232] 0.4762913 0.5161453 0.5638204 0.3688685 0.5419602 0.3998490 0.3929661
#> [239] 0.4932351 0.4345458 0.4882574 0.4715283 0.3504753 0.5192171 0.4680825
#> [246] 0.5922902 0.4249537 0.5123471 0.5606578 0.3976015 0.5292690 0.4021202
#> [253] 0.4838688 0.5798843 0.4565908 0.3898463 0.5543668 0.4237390 0.5114919
#> [260] 0.4884343 0.4240499 0.4710702 0.4657199 0.7084325 0.4810418 0.3768728
#> [267] 0.4623340 0.4704867 0.5496267 0.3881951 0.5170970 0.5081212 0.4607887
#> [274] 0.4627568 0.5372473 0.4485171 0.4233033 0.5293588 0.5153163 0.5700245
#> [281] 0.5198909 0.6414800 0.4757418 0.4522780 0.4170697 0.6550176 0.4850003
#> [288] 0.5942590 0.3825319 0.3862644 0.6434600 0.4920077 0.4448011 0.4674408
#> [295] 0.5058835 0.5085530 0.5189024 0.5127645 0.4098307 0.5958679 0.5477714
#> [302] 0.6001325 0.5012998 0.5897185 0.5954650 0.3765506 0.4791252 0.5686496
#> [309] 0.4930061 0.3435568 0.6058773 0.4854596 0.5298519 0.5236442 0.5375487
#> [316] 0.4501661 0.4380009 0.5527382 0.4815212 0.4891832 0.5450042 0.4369533
#> [323] 0.6023842 0.5707890 0.6554904 0.4512168 0.4715616 0.4028302 0.4863856
#> [330] 0.5051984 0.5204367 0.5557065 0.5394645 0.5687281 0.4933832 0.4508144
#> [337] 0.5540401 0.4908433 0.4387478 0.4592262 0.5332123 0.3978356 0.4151103
#> [344] 0.5463164 0.5086750 0.4756335 0.4489072 0.3575472 0.4701911 0.4992150
#> [351] 0.5383309 0.5152342 0.5927639 0.4806994 0.3720755 0.4870256 0.5112705
#> [358] 0.5074425 0.6288546 0.3840175 0.5111406 0.5767660 0.6064326 0.4247445
#> [365] 0.5451005 0.4811519 0.4396309 0.5060638 0.5041230 0.4339816 0.5478450
#> [372] 0.3815476 0.4408808 0.6263566 0.3728899 0.4927847 0.4328202 0.4345731
#> [379] 0.5315013 0.4820861 0.3817560 0.4185878 0.4139692 0.4541014 0.5446713
#> [386] 0.4815751 0.4819529 0.3634295 0.4757620 0.6693872 0.5392868 0.4937481
#> [393] 0.6603554 0.4604916 0.4222959 0.4810585 0.4956354 0.4645680 0.3552854
#> [400] 0.5628437 0.3830953 0.3962095 0.3743083 0.5044450 0.5450588 0.5358377
#> [407] 0.6198545 0.5807054 0.4156745 0.3380421 0.5349245 0.4917217 0.3900657
#> [414] 0.5010658 0.5545796 0.5342513 0.5809042 0.5584741 0.5557115 0.4518738
#> [421] 0.4285800 0.4671152 0.4991703 0.6554223 0.6506671 0.3598778 0.5096160
#> [428] 0.5810097 0.5740709 0.6464846 0.4107726 0.5649616 0.5698020 0.4840094
#> [435] 0.4175442 0.3636645 0.6446077 0.5984325 0.5614587 0.4357102 0.5329262
#> [442] 0.3952921 0.4947716 0.5661579 0.5380669 0.5580109 0.5457654 0.4963886
#> [449] 0.4459673 0.6332595 0.4539294 0.5317350 0.4524946 0.4918144 0.5736177
#> [456] 0.6352770 0.5009395 0.5297642 0.5457479 0.5497506 0.4905960 0.4301131
#> [463] 0.5253193 0.4640124 0.5462804 0.5877625 0.4801204 0.5577398 0.5847659
#> [470] 0.5046095 0.5187632 0.5181585 0.5724089 0.4642192 0.4551622 0.5646626
#> [477] 0.4826866 0.5593406 0.4482846 0.5507685 0.3553587 0.5213470 0.4716660
#> [484] 0.5449829 0.5470367 0.5944044 0.4692279 0.5126396 0.4978271 0.4437780
#> [491] 0.4402086 0.4693941 0.4675178 0.5364951 0.5976814 0.4406625 0.6471707
#> [498] 0.4221731 0.4536440 0.5121358 0.4232829 0.4867471 0.6295649 0.5138454
#> [505] 0.5088137 0.5136914 0.5972745 0.5227871 0.4145455 0.5345201 0.5008895
#> [512] 0.5599126 0.5929579 0.5460928 0.5154563 0.4846953 0.5133568 0.4128998
#> [519] 0.4937223 0.4296853 0.5992189 0.4558682 0.5882198 0.6449526 0.4455901
#> [526] 0.4497379 0.5128254 0.4991080 0.5206306 0.4419576 0.3652884 0.4457943
#> [533] 0.6107181 0.4558825 0.4855425 0.5099634 0.5521335 0.6624957 0.5412059
#> [540] 0.5135115 0.4811479 0.5004091 0.5083518 0.3742850 0.5264742 0.5958283
#> [547] 0.5777330 0.4986829 0.4749131 0.4625081 0.4452079 0.5290024 0.6055547
#> [554] 0.4367076 0.5406056 0.4820461 0.4348487 0.3967229 0.4936950 0.4724594
#> [561] 0.4499461 0.4378674 0.4752048 0.4782139 0.5461926 0.5214747 0.4073590
#> [568] 0.5291057 0.3897328 0.4748659 0.4471624 0.4585773 0.6083582 0.5023974
#> [575] 0.4464478 0.5810185 0.5213156 0.4502039 0.7222726 0.5225398 0.4829156
#> [582] 0.5711364 0.4475545 0.6054778 0.4535213 0.4801495 0.6600248 0.3897687
#> [589] 0.4992014 0.4540852 0.4509975 0.4131182 0.5338565 0.4906406 0.5337476
#> [596] 0.3725658 0.5133403 0.6094682 0.5160436 0.5090790 0.4015149 0.5459253
#> [603] 0.4430419 0.5411878 0.4498092 0.4436413 0.4285790 0.4259861 0.6447146
#> [610] 0.5059503 0.4791670 0.5797756 0.6937951 0.5161121 0.4204348 0.5661795
#> [617] 0.5070066 0.6065221 0.4360698 0.4810825 0.4602759 0.5342654 0.5719467
#> [624] 0.5306375 0.4729576 0.5195784 0.4869170 0.6245200 0.6010015 0.4833965
#> [631] 0.3801312 0.4474624 0.4352136 0.5717723 0.5427909 0.6731110 0.6369104
#> [638] 0.5091189 0.4175586 0.3960396 0.6126213 0.3862221 0.4572167 0.3506560
#> [645] 0.4817026 0.4475391 0.5075578 0.5217977 0.5425487 0.3761043 0.5536365
#> [652] 0.4561190 0.3615489 0.5071856 0.4939222 0.3877988 0.5705991 0.5778204
#> [659] 0.5199564 0.4456409 0.6607956 0.5164931 0.4788334 0.4455812 0.4515707
#> [666] 0.4038421 0.3950178 0.4348304 0.6610873 0.4808166 0.4445586 0.5757088
#> [673] 0.4987007 0.5282900 0.5764054 0.5564176 0.5949310 0.3547364 0.5129071
#> [680] 0.5111752 0.4908386 0.5298425 0.5177828 0.5046744 0.6015479 0.4637610
#> [687] 0.4566255 0.5296141 0.5573319 0.3852895 0.4308149 0.4576272 0.3792412
#> [694] 0.4658366 0.5128782 0.4060741 0.5469712 0.4828777 0.6783695 0.4363770
#> [701] 0.4857666 0.4407669 0.5271829 0.4677413 0.4681256 0.4800061 0.4907712
#> [708] 0.5176389 0.4918926 0.5330977 0.4735092 0.6529030 0.5943272 0.5556262
#> [715] 0.5399628 0.4667436 0.5431649 0.4452479 0.5458686 0.4422522 0.5434875
#> [722] 0.3644541 0.4304718 0.5250357 0.5380671 0.4323499 0.4996843 0.5425564
#> [729] 0.6755070 0.4877131 0.5620808 0.4564400 0.6036523 0.4090183 0.4876906
#> [736] 0.5016068 0.5646113 0.4308509 0.3521050 0.5608032 0.4815001 0.4696397
#> [743] 0.4751283 0.4650957 0.4897964 0.4439550 0.4575170 0.5035323 0.6656998
#> [750] 0.5802614 0.5720451 0.4586973 0.4814499 0.5126396 0.6108490 0.4172794
#> [757] 0.4110166 0.5039464 0.4267424 0.6688915 0.4787295 0.4443856 0.5751088
#> [764] 0.5229602 0.5167265 0.4974418 0.4512452 0.4288275 0.5435783 0.3318656
#> [771] 0.5001083 0.4174917 0.5468099 0.5047170 0.5682110 0.6530065 0.5218896
#> [778] 0.4717107 0.4648549 0.6387392 0.4998142 0.4531829 0.5730514 0.5546815
#> [785] 0.5410733 0.5721663 0.4219625 0.5430288 0.5586265 0.4271782 0.5100890
#> [792] 0.5092021 0.4776515 0.5051277 0.6146411 0.4776893 0.3961631 0.4304136
#> [799] 0.4989729 0.4623296 0.6037941 0.5873997 0.4357187 0.4978724 0.5109339
#> [806] 0.5367925 0.5154140 0.5021866 0.6244890 0.5662031 0.5219311 0.4755347
#> [813] 0.4251277 0.5297801 0.5180446 0.3866047 0.5816505 0.4524774 0.6626180
#> [820] 0.4502557 0.5191250 0.6351960 0.6634165 0.6280570 0.4264477 0.5538956
#> [827] 0.5838384 0.4908666 0.4828843 0.4039426 0.4271170 0.5562554 0.5251581
#> [834] 0.5853020 0.3699575 0.4949258 0.5890193 0.5693055 0.5761202 0.5635758
#> [841] 0.5454900 0.5715322 0.5364154 0.3387994 0.4704680 0.5152128 0.5542944
#> [848] 0.4103741 0.5071275 0.5976424 0.4618195 0.4578329 0.4738265 0.4501294
#> [855] 0.7909680 0.6068832 0.6099551 0.5593130 0.5329134 0.5736117 0.4439891
#> [862] 0.4945144 0.4592826 0.5802193 0.3860988 0.4437521 0.4995632 0.3468886
#> [869] 0.3995971 0.4500668 0.6221863 0.4440518 0.4634099 0.4346437 0.4768583
#> [876] 0.5487000 0.4204362 0.6775302 0.6127672 0.4720481 0.5552371 0.3872892
#> [883] 0.4868686 0.3341203 0.4968669 0.5225002 0.4520126 0.4047058 0.5086684
#> [890] 0.4524827 0.5013577 0.3868026 0.3753252 0.5913437 0.3334542 0.5115515
#> [897] 0.4493568 0.4549822 0.4379730 0.5166218 0.5348588 0.5358250 0.5737149
#> [904] 0.5490975 0.4951617 0.6064066 0.5463536 0.5781418 0.5106181 0.4165318
#> [911] 0.5317101 0.5943065 0.4394744 0.4776687 0.7115416 0.5454630 0.4357009
#> [918] 0.4750110 0.4833883 0.4608972 0.4534894 0.5566896 0.5101504 0.3549225
#> [925] 0.4628177 0.5285132 0.5109511 0.6400622 0.4580895 0.4262192 0.3817799
#> [932] 0.6222056 0.2849699 0.4326163 0.4901917 0.4898586 0.5966746 0.3848488
#> [939] 0.4445275 0.5138854 0.6154511 0.6329817 0.4193105 0.5883061 0.5157285
#> [946] 0.4998797 0.4780508 0.5123998 0.5040942 0.5538482 0.6272771 0.4205645
#> [953] 0.4510933 0.4046009 0.5630498 0.5562685 0.4321900 0.4635401 0.4798476
#> [960] 0.5072167 0.5122810 0.4446438 0.4978450 0.4518649 0.5238761 0.5629303
#> [967] 0.4680304 0.5093791 0.5465368 0.6122504 0.4316976 0.5417523 0.5004860
#> [974] 0.5135580 0.5935662 0.5156883 0.6130760 0.5589853 0.4403891 0.6796962
#> [981] 0.4731758 0.4561493 0.4718228 0.4971397 0.4644658 0.5744838 0.5169383
#> [988] 0.5286844 0.6139006 0.5195006 0.4001353 0.6076444 0.4533157 0.5372002
#> [995] 0.5476565 0.4384211 0.5142171 0.4898244 0.3755558 0.5340389