Relative sea level rate (RSL) estimation
BchronRSL(
BchronologyRun,
RSLmean,
RSLsd,
degree = 1,
iterations = 10000,
burn = 2000,
thin = 8
)Arguments
- BchronologyRun
Output from a run of
Bchronology- RSLmean
A vector of RSL mean estimates of the same length as the number of predictPositions given to the
Bchronologyfunction- RSLsd
A vector RSL standard deviations of the same length as the number of predictPositions given to the
Bchronologyfunction- degree
The degree of the polynomial regression: linear=1 (default), quadratic=2, etc. Supports up to degree 5, though this will depend on the data given
- iterations
The number of MCMC iterations to run
- burn
The number of starting iterations to discard
- thin
The step size of iterations to discard
Value
An object of class BchronRSLRun with elements itemize
Details
This function fits an errors-in-variables regression model to relative sea level (RSL) data. An errors-in-variables regression model allows for uncertainty in the explanatory variable, here the age of sea level data point. The algorithm is more fully defined in the reference below
References
Andrew C. Parnell and W. Roland Gehrels (2013) 'Using chronological models in late holocene sea level reconstructions from salt marsh sediments' In: I. Shennan, B.P. Horton, and A.J. Long (eds). Handbook of Sea Level Research. Chichester: Wiley
See also
Examples
# \donttest{
# Load in data
data(TestChronData)
data(TestRSLData)
# Run through Bchronology
RSLrun <- with(TestChronData, Bchronology(
ages = ages,
ageSds = ageSds,
positions = position,
positionThicknesses = thickness,
ids = id,
calCurves = calCurves,
predictPositions = TestRSLData$Depth
))
#> ages not given as whole numbers - rounding occurred
#> ageSds not given as whole numbers - rounding occurred
#> ages not given as whole numbers - rounding occurred
#> ageSds not given as whole numbers - rounding occurred
#> ages not given as whole numbers - rounding occurred
#> ageSds not given as whole numbers - rounding occurred
#> Running Bchronology...
#>
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#> Run completed!
# Now run through BchronRSL
RSLrun2 <- BchronRSL(RSLrun, RSLmean = TestRSLData$RSL, RSLsd = TestRSLData$Sigma, degree = 3)
#>
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# Summarise it
summary(RSLrun2)
#> Posterior Medians with 95% credible intervals...
#> Power Lower Median Upper
#> mean -0.8297 -0.6565 -0.4821
#> linear -0.803 -0.479 -0.1422
#> quadratic -0.1982 0.3028 0.7821
#> cubic -0.8903 -0.3645 0.1509
#> Age RSL_2.5 RSL_50 RSL_97.5
#> 1 1954.950000 -1.7792303 -1.49688070 -1.262837878
#> 2 1935.071717 -1.7355972 -1.46766019 -1.249417899
#> 3 1915.193434 -1.6895572 -1.43988813 -1.227267491
#> 4 1895.315152 -1.6498504 -1.41311500 -1.205676956
#> 5 1875.436869 -1.6066464 -1.38918212 -1.188720999
#> 6 1855.558586 -1.5752198 -1.36531219 -1.166442383
#> 7 1835.680303 -1.5447318 -1.34216149 -1.149316120
#> 8 1815.802020 -1.5150796 -1.31709566 -1.132630752
#> 9 1795.923737 -1.4900465 -1.29668943 -1.111810937
#> 10 1776.045455 -1.4679242 -1.27497809 -1.091303147
#> 11 1756.167172 -1.4412127 -1.25493712 -1.072516111
#> 12 1736.288889 -1.4148414 -1.23426320 -1.053314921
#> 13 1716.410606 -1.3961974 -1.21162568 -1.031063143
#> 14 1696.532323 -1.3794423 -1.19222667 -1.009030935
#> 15 1676.654040 -1.3586505 -1.17383306 -0.992632522
#> 16 1656.775758 -1.3408142 -1.15539480 -0.976556386
#> 17 1636.897475 -1.3250422 -1.13653846 -0.956058809
#> 18 1617.019192 -1.3075500 -1.12008061 -0.940616179
#> 19 1597.140909 -1.2927219 -1.10435826 -0.922267545
#> 20 1577.262626 -1.2788331 -1.08755477 -0.906110691
#> 21 1557.384343 -1.2656868 -1.07085838 -0.891895381
#> 22 1537.506061 -1.2508469 -1.05611009 -0.878320450
#> 23 1517.627778 -1.2364538 -1.04135043 -0.864108867
#> 24 1497.749495 -1.2204347 -1.02733406 -0.851765424
#> 25 1477.871212 -1.2074010 -1.01321931 -0.835894170
#> 26 1457.992929 -1.1928376 -1.00043216 -0.826840794
#> 27 1438.114646 -1.1780057 -0.98772721 -0.816035332
#> 28 1418.236364 -1.1631599 -0.97557137 -0.803671701
#> 29 1398.358081 -1.1488917 -0.96276858 -0.791577088
#> 30 1378.479798 -1.1375788 -0.95159393 -0.780511521
#> 31 1358.601515 -1.1240698 -0.94182116 -0.769959463
#> 32 1338.723232 -1.1105627 -0.93188602 -0.760964646
#> 33 1318.844949 -1.0982343 -0.92124388 -0.754577107
#> 34 1298.966667 -1.0843843 -0.91088112 -0.748150848
#> 35 1279.088384 -1.0669713 -0.90128898 -0.742343446
#> 36 1259.210101 -1.0511535 -0.89184316 -0.737742897
#> 37 1239.331818 -1.0363282 -0.88223687 -0.733921063
#> 38 1219.453535 -1.0242071 -0.87316165 -0.727144987
#> 39 1199.575253 -1.0159876 -0.86343387 -0.719254858
#> 40 1179.696970 -1.0062733 -0.85476472 -0.714324831
#> 41 1159.818687 -0.9911835 -0.84513304 -0.707468082
#> 42 1139.940404 -0.9783273 -0.83719869 -0.699699105
#> 43 1120.062121 -0.9676948 -0.82923296 -0.691948677
#> 44 1100.183838 -0.9544609 -0.82222590 -0.685083580
#> 45 1080.305556 -0.9422840 -0.81496298 -0.678778328
#> 46 1060.427273 -0.9349156 -0.80608938 -0.673901234
#> 47 1040.548990 -0.9276126 -0.79874395 -0.666143686
#> 48 1020.670707 -0.9160466 -0.79079646 -0.659080346
#> 49 1000.792424 -0.9074359 -0.78345770 -0.651926825
#> 50 980.914141 -0.8949794 -0.77643851 -0.641194364
#> 51 961.035859 -0.8891237 -0.76990171 -0.631783827
#> 52 941.157576 -0.8866424 -0.76187587 -0.621162563
#> 53 921.279293 -0.8829105 -0.75417311 -0.610580262
#> 54 901.401010 -0.8755046 -0.74629117 -0.599977597
#> 55 881.522727 -0.8728845 -0.73723182 -0.587775210
#> 56 861.644444 -0.8648175 -0.72905200 -0.578998859
#> 57 841.766162 -0.8588808 -0.71989661 -0.568598976
#> 58 821.887879 -0.8576554 -0.71282391 -0.558259983
#> 59 802.009596 -0.8554900 -0.70437457 -0.547550074
#> 60 782.131313 -0.8490077 -0.69629973 -0.535974434
#> 61 762.253030 -0.8472929 -0.68846016 -0.522567013
#> 62 742.374747 -0.8430725 -0.67982392 -0.513137632
#> 63 722.496465 -0.8392636 -0.67060546 -0.499303808
#> 64 702.618182 -0.8315349 -0.66273785 -0.490172270
#> 65 682.739899 -0.8287070 -0.65365930 -0.477355412
#> 66 662.861616 -0.8214991 -0.64492525 -0.464699870
#> 67 642.983333 -0.8150763 -0.63444833 -0.452700571
#> 68 623.105051 -0.8072613 -0.62407625 -0.437572020
#> 69 603.226768 -0.7989685 -0.61283576 -0.424074634
#> 70 583.348485 -0.7912690 -0.60157704 -0.412619532
#> 71 563.470202 -0.7830976 -0.59128653 -0.399277489
#> 72 543.591919 -0.7752511 -0.58064423 -0.386007459
#> 73 523.713636 -0.7662794 -0.56832706 -0.372752929
#> 74 503.835354 -0.7561338 -0.55531935 -0.358714414
#> 75 483.957071 -0.7438722 -0.54228879 -0.347642894
#> 76 464.078788 -0.7319868 -0.52904603 -0.336824040
#> 77 444.200505 -0.7183439 -0.51537541 -0.326382909
#> 78 424.322222 -0.7043262 -0.50180962 -0.316118034
#> 79 404.443939 -0.6871740 -0.48757898 -0.304667464
#> 80 384.565657 -0.6691682 -0.47225196 -0.291695076
#> 81 364.687374 -0.6507678 -0.45746576 -0.278769384
#> 82 344.809091 -0.6319135 -0.44210804 -0.265895092
#> 83 324.930808 -0.6127118 -0.42597442 -0.252770022
#> 84 305.052525 -0.5923549 -0.40916109 -0.238033317
#> 85 285.174242 -0.5679557 -0.38995820 -0.224604010
#> 86 265.295960 -0.5404045 -0.37118935 -0.213012860
#> 87 245.417677 -0.5138594 -0.35197042 -0.197942838
#> 88 225.539394 -0.4872510 -0.33231119 -0.182729174
#> 89 205.661111 -0.4608591 -0.31133339 -0.170755763
#> 90 185.782828 -0.4361089 -0.28935481 -0.152539868
#> 91 165.904545 -0.4051368 -0.26890699 -0.137501712
#> 92 146.026263 -0.3782835 -0.24594454 -0.121844528
#> 93 126.147980 -0.3532300 -0.22403691 -0.102913780
#> 94 106.269697 -0.3241525 -0.20089763 -0.081297829
#> 95 86.391414 -0.2957087 -0.17626508 -0.058970673
#> 96 66.513131 -0.2758915 -0.15132802 -0.035026193
#> 97 46.634848 -0.2470937 -0.12537710 -0.007057105
#> 98 26.756566 -0.2249098 -0.09926228 0.024439868
#> 99 6.878283 -0.2088265 -0.07086890 0.061546721
#> 100 -13.000000 -0.1942601 -0.04058532 0.104871118
#> Age RSL_rate_2.5 RSL_rate_50 RSL_rate_97.5
#> 1 1954.950000 0.331239687 1.4333170 2.6834612
#> 2 1935.071717 0.347404262 1.3947777 2.5800033
#> 3 1915.193434 0.363089192 1.3538212 2.4879322
#> 4 1895.315152 0.378252868 1.3154830 2.3975037
#> 5 1875.436869 0.391826656 1.2783705 2.2915601
#> 6 1855.558586 0.391573647 1.2392100 2.2029731
#> 7 1835.680303 0.394666241 1.1985697 2.1162294
#> 8 1815.802020 0.420872155 1.1603686 2.0369776
#> 9 1795.923737 0.429429634 1.1238456 1.9480200
#> 10 1776.045455 0.434645492 1.0884906 1.8604859
#> 11 1756.167172 0.438751297 1.0545462 1.7732040
#> 12 1736.288889 0.437833674 1.0133401 1.6967904
#> 13 1716.410606 0.443044742 0.9831227 1.6337557
#> 14 1696.532323 0.448907705 0.9514755 1.5711238
#> 15 1676.654040 0.448206333 0.9246791 1.5047866
#> 16 1656.775758 0.449536226 0.8947120 1.4290037
#> 17 1636.897475 0.444895403 0.8714732 1.3664604
#> 18 1617.019192 0.443003270 0.8451007 1.2934481
#> 19 1597.140909 0.433826437 0.8172606 1.2368838
#> 20 1577.262626 0.430602025 0.7900166 1.1862863
#> 21 1557.384343 0.415176493 0.7626598 1.1331920
#> 22 1537.506061 0.410427249 0.7358791 1.0958328
#> 23 1517.627778 0.393181016 0.7150595 1.0543629
#> 24 1497.749495 0.385329673 0.6930159 1.0164300
#> 25 1477.871212 0.374493140 0.6698893 0.9870861
#> 26 1457.992929 0.363009994 0.6489823 0.9625096
#> 27 1438.114646 0.337102553 0.6286474 0.9281373
#> 28 1418.236364 0.310683713 0.6087329 0.9090128
#> 29 1398.358081 0.286462421 0.5879548 0.8948693
#> 30 1378.479798 0.256044302 0.5713806 0.8823946
#> 31 1358.601515 0.235436647 0.5523628 0.8615768
#> 32 1338.723232 0.211844587 0.5411869 0.8712973
#> 33 1318.844949 0.188313201 0.5257649 0.8699756
#> 34 1298.966667 0.170150052 0.5113863 0.8684135
#> 35 1279.088384 0.147361196 0.4921062 0.8673539
#> 36 1259.210101 0.125500526 0.4821293 0.8693252
#> 37 1239.331818 0.106602806 0.4675674 0.8613979
#> 38 1219.453535 0.081807095 0.4543476 0.8587381
#> 39 1199.575253 0.061556498 0.4470471 0.8568608
#> 40 1179.696970 0.043524839 0.4368494 0.8520846
#> 41 1159.818687 0.023086651 0.4296365 0.8463265
#> 42 1139.940404 0.003396660 0.4237116 0.8423770
#> 43 1120.062121 -0.012540897 0.4155395 0.8425991
#> 44 1100.183838 -0.025152519 0.4092213 0.8369356
#> 45 1080.305556 -0.035525877 0.4030438 0.8337879
#> 46 1060.427273 -0.044940068 0.3956902 0.8287237
#> 47 1040.548990 -0.051839050 0.3915129 0.8264740
#> 48 1020.670707 -0.056809528 0.3894167 0.8238583
#> 49 1000.792424 -0.059835818 0.3864308 0.8210116
#> 50 980.914141 -0.056914637 0.3849282 0.8168793
#> 51 961.035859 -0.057503033 0.3846426 0.8158140
#> 52 941.157576 -0.055956836 0.3856787 0.8134002
#> 53 921.279293 -0.052286938 0.3880119 0.8151069
#> 54 901.401010 -0.046563056 0.3900258 0.8140691
#> 55 881.522727 -0.038382838 0.3907748 0.8164538
#> 56 861.644444 -0.028528785 0.3964450 0.8138081
#> 57 841.766162 -0.016365279 0.4024447 0.8109428
#> 58 821.887879 -0.001279767 0.4096177 0.8067872
#> 59 802.009596 0.015230535 0.4172969 0.8069080
#> 60 782.131313 0.033540791 0.4289716 0.7993152
#> 61 762.253030 0.053815958 0.4368655 0.8006888
#> 62 742.374747 0.076668153 0.4462958 0.7995322
#> 63 722.496465 0.101666145 0.4547387 0.7954833
#> 64 702.618182 0.124849064 0.4686488 0.7983969
#> 65 682.739899 0.152774044 0.4822843 0.8028740
#> 66 662.861616 0.180082552 0.4945585 0.8044899
#> 67 642.983333 0.211629607 0.5078096 0.8060876
#> 68 623.105051 0.237881358 0.5217219 0.8023811
#> 69 603.226768 0.268045226 0.5357624 0.8008854
#> 70 583.348485 0.299935009 0.5525638 0.8020850
#> 71 563.470202 0.326876739 0.5705978 0.8038531
#> 72 543.591919 0.358186692 0.5895482 0.8103234
#> 73 523.713636 0.391985793 0.6073065 0.8224678
#> 74 503.835354 0.417815643 0.6270493 0.8341598
#> 75 483.957071 0.445394387 0.6459431 0.8518181
#> 76 464.078788 0.467789449 0.6681708 0.8669137
#> 77 444.200505 0.472345250 0.6890330 0.8926972
#> 78 424.322222 0.473469256 0.7152638 0.9308982
#> 79 404.443939 0.492163333 0.7369924 0.9700114
#> 80 384.565657 0.495237606 0.7599331 1.0051191
#> 81 364.687374 0.492575490 0.7874077 1.0582547
#> 82 344.809091 0.495872974 0.8163273 1.1167708
#> 83 324.930808 0.497321126 0.8460421 1.1768980
#> 84 305.052525 0.497703287 0.8731013 1.2387086
#> 85 285.174242 0.485455140 0.9022281 1.2951456
#> 86 265.295960 0.471329968 0.9321213 1.3595177
#> 87 245.417677 0.457132596 0.9644476 1.4293562
#> 88 225.539394 0.443631336 0.9979295 1.5063280
#> 89 205.661111 0.432500014 1.0326864 1.5810393
#> 90 185.782828 0.420033887 1.0655681 1.6596941
#> 91 165.904545 0.411186483 1.0985466 1.7486503
#> 92 146.026263 0.401071116 1.1311893 1.8238104
#> 93 126.147980 0.382774366 1.1641020 1.9095777
#> 94 106.269697 0.369964653 1.2002292 1.9949352
#> 95 86.391414 0.356948699 1.2347835 2.0788550
#> 96 66.513131 0.343726505 1.2698006 2.1646221
#> 97 46.634848 0.330309187 1.3077843 2.2670972
#> 98 26.756566 0.315515503 1.3469361 2.3643929
#> 99 6.878283 0.298146514 1.3851205 2.4611151
#> 100 -13.000000 0.278612004 1.4277227 2.5580616
#> Age RSL_accel_2.5 RSL_accel_50 RSL_accel_97.5
#> 1 1954.950000 -5.2432445 -2.19862379 0.8529778
#> 2 1935.071717 -5.1370871 -2.15910994 0.8418115
#> 3 1915.193434 -5.0309297 -2.11778906 0.8263702
#> 4 1895.315152 -4.9247723 -2.07556546 0.8012485
#> 5 1875.436869 -4.8226945 -2.02975886 0.7760736
#> 6 1855.558586 -4.7220542 -1.98285134 0.7505200
#> 7 1835.680303 -4.6214139 -1.94257664 0.7249664
#> 8 1815.802020 -4.5207736 -1.90078912 0.7065147
#> 9 1795.923737 -4.4201333 -1.85840984 0.6925211
#> 10 1776.045455 -4.3194931 -1.81710472 0.6753328
#> 11 1756.167172 -4.2188528 -1.76403420 0.6601707
#> 12 1736.288889 -4.1182125 -1.71771579 0.6458275
#> 13 1716.410606 -4.0143336 -1.67251257 0.6332375
#> 14 1696.532323 -3.9086692 -1.62045573 0.6206474
#> 15 1676.654040 -3.8030049 -1.58039729 0.6080573
#> 16 1656.775758 -3.6973405 -1.53399089 0.5954673
#> 17 1636.897475 -3.5916762 -1.48689255 0.5828772
#> 18 1617.019192 -3.4860118 -1.44223914 0.5701774
#> 19 1597.140909 -3.3803475 -1.39333267 0.5574287
#> 20 1577.262626 -3.2745603 -1.34549460 0.5437575
#> 21 1557.384343 -3.1687219 -1.30351293 0.5253304
#> 22 1537.506061 -3.0734239 -1.25649096 0.5044618
#> 23 1517.627778 -2.9819720 -1.21012566 0.4885721
#> 24 1497.749495 -2.8793717 -1.16721777 0.4703820
#> 25 1477.871212 -2.7720972 -1.12860653 0.4521918
#> 26 1457.992929 -2.6649682 -1.08733282 0.4339038
#> 27 1438.114646 -2.5575642 -1.03681926 0.4170886
#> 28 1418.236364 -2.4556730 -0.98603452 0.4019142
#> 29 1398.358081 -2.3521085 -0.93716842 0.3867398
#> 30 1378.479798 -2.2569275 -0.88776382 0.3775309
#> 31 1358.601515 -2.1707072 -0.83916080 0.3728330
#> 32 1338.723232 -2.0844044 -0.79470423 0.3681350
#> 33 1318.844949 -1.9793694 -0.74666023 0.3632609
#> 34 1298.966667 -1.8981386 -0.70524304 0.3586299
#> 35 1279.088384 -1.8004466 -0.65935024 0.3334807
#> 36 1259.210101 -1.6936361 -0.62025248 0.3185358
#> 37 1239.331818 -1.5870914 -0.57857882 0.3303131
#> 38 1219.453535 -1.4838046 -0.52688278 0.3207750
#> 39 1199.575253 -1.3949647 -0.48514004 0.3054927
#> 40 1179.696970 -1.3028865 -0.44662916 0.2927400
#> 41 1159.818687 -1.2049119 -0.40619570 0.2891235
#> 42 1139.940404 -1.1095218 -0.35824329 0.2756944
#> 43 1120.062121 -1.0137945 -0.31821882 0.2791767
#> 44 1100.183838 -0.9060541 -0.27917031 0.2810483
#> 45 1080.305556 -0.8225465 -0.23644476 0.2770068
#> 46 1060.427273 -0.7311543 -0.19425312 0.2994099
#> 47 1040.548990 -0.6634211 -0.15815388 0.3134845
#> 48 1020.670707 -0.5922852 -0.11268127 0.3342135
#> 49 1000.792424 -0.5281114 -0.07031497 0.3644910
#> 50 980.914141 -0.4640736 -0.02423284 0.3994831
#> 51 961.035859 -0.4305303 0.02085339 0.4498001
#> 52 941.157576 -0.3901382 0.06148577 0.5163450
#> 53 921.279293 -0.3577304 0.10356259 0.5695735
#> 54 901.401010 -0.3211839 0.14861896 0.6375484
#> 55 881.522727 -0.3227591 0.19168364 0.7161333
#> 56 861.644444 -0.3172720 0.23231760 0.7850889
#> 57 841.766162 -0.3301233 0.27617052 0.8648532
#> 58 821.887879 -0.3316640 0.31947249 0.9515076
#> 59 802.009596 -0.3412360 0.36041256 1.0489288
#> 60 782.131313 -0.3386620 0.40499012 1.1362769
#> 61 762.253030 -0.3580228 0.44788142 1.2237316
#> 62 742.374747 -0.3616457 0.48885747 1.3176395
#> 63 722.496465 -0.3686942 0.53006102 1.4045584
#> 64 702.618182 -0.3897308 0.57407309 1.5044820
#> 65 682.739899 -0.3997171 0.61745624 1.5954947
#> 66 662.861616 -0.4097033 0.65881282 1.6947077
#> 67 642.983333 -0.4196896 0.70781143 1.7925865
#> 68 623.105051 -0.4295333 0.75191853 1.8918742
#> 69 603.226768 -0.4462183 0.79442033 1.9942500
#> 70 583.348485 -0.4704566 0.83488943 2.0939846
#> 71 563.470202 -0.4946950 0.87686887 2.1896951
#> 72 543.591919 -0.5110911 0.91574755 2.2957493
#> 73 523.713636 -0.5130915 0.96075486 2.3892618
#> 74 503.835354 -0.5150320 1.00401802 2.4944046
#> 75 483.957071 -0.5294933 1.04797778 2.5873807
#> 76 464.078788 -0.5355714 1.09172095 2.6747742
#> 77 444.200505 -0.5373795 1.14240590 2.7932931
#> 78 424.322222 -0.5592258 1.18027382 2.9155526
#> 79 404.443939 -0.5728286 1.22435877 3.0180082
#> 80 384.565657 -0.5816966 1.26840384 3.1203840
#> 81 364.687374 -0.5904420 1.31359422 3.2227598
#> 82 344.809091 -0.6107390 1.36012326 3.3251356
#> 83 324.930808 -0.6246567 1.41114971 3.4275114
#> 84 305.052525 -0.6377398 1.45557458 3.5298873
#> 85 285.174242 -0.6558978 1.49564880 3.6332576
#> 86 265.295960 -0.6630047 1.54054454 3.7366370
#> 87 245.417677 -0.6686603 1.58215808 3.8389101
#> 88 225.539394 -0.6929746 1.62676056 3.9409591
#> 89 205.661111 -0.7215619 1.67429818 4.0454256
#> 90 185.782828 -0.7481789 1.71946072 4.1527823
#> 91 165.904545 -0.7646007 1.76278588 4.2562384
#> 92 146.026263 -0.7792517 1.80188320 4.3604728
#> 93 126.147980 -0.7958392 1.84232416 4.4710757
#> 94 106.269697 -0.8175590 1.88832436 4.5816786
#> 95 86.391414 -0.8355728 1.93291214 4.6904284
#> 96 66.513131 -0.8589041 1.97541579 4.7883649
#> 97 46.634848 -0.8773806 2.02249005 4.8843004
#> 98 26.756566 -0.8891658 2.07006666 4.9926554
#> 99 6.878283 -0.8987528 2.11554255 5.1033952
#> 100 -13.000000 -0.9081147 2.15856074 5.2141351
# Plot it
plot(RSLrun2)
# }