Default class for candidate changepoint sets
seg_basket.RdDefault class for candidate changepoint sets
Arguments
- x
a numeric vector coercible into a
stats::ts()object- algorithm
Algorithm used to find the changepoints
- cpt_list
a possibly empty
list()of candidate changepoints- seg_params
a possibly empty
list()of segmenter parameters- model_name
character indicating the model used to find the changepoints.
- penalty
character indicating the name of the penalty function used to find the changepoints.
- ...
currently ignored
Examples
seg <- seg_basket(DataCPSim, cpt_list = list(c(365), c(330, 839)))
str(seg)
#> List of 6
#> $ data : Time-Series [1:1096] from 1 to 1096: 35.5 29 35.6 33 29.5 ...
#> $ algorithm : logi NA
#> $ basket : tibble [2 × 7] (S3: tbl_df/tbl/data.frame)
#> ..$ changepoints:List of 2
#> .. ..$ : num 365
#> .. ..$ : num [1:2] 330 839
#> ..$ model :List of 2
#> .. ..$ :List of 6
#> .. .. ..$ data : Time-Series [1:1096] from 1 to 1096: 35.5 29 35.6 33 29.5 ...
#> .. .. ..$ tau : num 365
#> .. .. ..$ region_params: tibble [2 × 2] (S3: tbl_df/tbl/data.frame)
#> .. .. .. ..$ region : chr [1:2] "[0,365)" "[365,1.1e+03]"
#> .. .. .. ..$ param_mu: num [1:2] 35.8 76.8
#> .. .. ..$ model_params : Named num 1716
#> .. .. .. ..- attr(*, "names")= chr "sigma_hatsq"
#> .. .. ..$ fitted_values: num [1:1096] 35.8 35.8 35.8 35.8 35.8 ...
#> .. .. ..$ model_name : chr "meanshift_norm"
#> .. .. ..- attr(*, "class")= chr "mod_cpt"
#> .. ..$ :List of 6
#> .. .. ..$ data : Time-Series [1:1096] from 1 to 1096: 35.5 29 35.6 33 29.5 ...
#> .. .. ..$ tau : num [1:2] 330 839
#> .. .. ..$ region_params: tibble [3 × 2] (S3: tbl_df/tbl/data.frame)
#> .. .. .. ..$ region : chr [1:3] "[0,330)" "[330,839)" "[839,1.1e+03]"
#> .. .. .. ..$ param_mu: num [1:3] 35.9 49.2 125.6
#> .. .. ..$ model_params : Named num 858
#> .. .. .. ..- attr(*, "names")= chr "sigma_hatsq"
#> .. .. ..$ fitted_values: num [1:1096] 35.9 35.9 35.9 35.9 35.9 ...
#> .. .. ..$ model_name : chr "meanshift_norm"
#> .. .. ..- attr(*, "class")= chr "mod_cpt"
#> ..$ logLik : num [1:2] -5636 -5256
#> ..$ AIC : num [1:2] 11281 10525
#> ..$ BIC : num [1:2] 11301 10555
#> ..$ MBIC : num [1:2] 11292 10551
#> ..$ MDL : num [1:2] 11306 10566
#> $ seg_params: list()
#> $ model_name: chr "meanshift_norm"
#> $ penalty : chr "BIC"
#> - attr(*, "class")= chr "seg_basket"
as.ts(seg)
#> Time Series:
#> Start = 1
#> End = 1096
#> Frequency = 1
#> [1] 35.50961 29.00292 35.63508 32.98452 29.53557 25.40781 28.82497
#> [8] 50.31157 24.93185 58.88063 30.35777 33.66315 32.58653 42.78788
#> [15] 45.23963 23.66417 20.00954 31.64746 34.65507 68.49028 43.53948
#> [22] 25.29938 57.19244 39.51995 23.79025 27.81451 42.00712 36.09812
#> [29] 32.74664 34.73679 60.20919 55.52211 33.92043 32.48948 22.66494
#> [36] 24.16119 27.05582 16.09789 31.69439 27.22202 20.64027 33.97673
#> [43] 46.71000 25.28389 24.88207 41.75347 36.50448 35.98297 31.39612
#> [50] 44.14153 67.82557 26.81619 27.55292 30.77449 51.17371 51.34317
#> [57] 23.10056 22.92962 29.39409 73.67531 23.46017 35.36286 29.45083
#> [64] 54.18062 25.04895 27.47914 51.41767 32.30387 43.17916 30.11288
#> [71] 22.45535 33.70278 34.16720 44.64931 22.60994 50.26498 50.28394
#> [78] 33.24944 38.73890 36.75336 52.38881 36.62906 16.68155 35.12389
#> [85] 35.89239 61.81050 47.85419 30.26446 36.93150 54.81053 30.32479
#> [92] 37.46579 49.93442 46.01734 24.86685 35.88435 42.25720 37.78741
#> [99] 46.26335 38.52976 47.99867 44.28395 51.05976 50.99393 36.01026
#> [106] 37.44409 16.77029 31.05583 22.40344 27.22149 28.31583 58.06805
#> [113] 38.30690 47.26490 31.55811 47.63268 23.38334 33.30157 46.75618
#> [120] 30.46511 23.17060 31.52724 38.55479 35.54940 49.63486 38.85458
#> [127] 35.80205 24.50227 20.49025 31.59546 33.84992 30.02572 23.84156
#> [134] 27.92167 28.04857 55.54324 23.82133 46.27102 35.95369 47.65766
#> [141] 31.37265 37.43892 26.73598 39.78209 37.23990 38.69749 25.74961
#> [148] 15.00954 41.03282 35.55822 28.20253 34.25572 36.72560 25.87219
#> [155] 34.25647 41.05718 45.99951 35.09617 30.10936 56.29692 21.62607
#> [162] 32.16878 48.08144 27.56512 24.86829 23.20973 23.35380 24.87480
#> [169] 41.98302 43.00026 42.37708 57.59545 28.58172 35.77870 28.82814
#> [176] 35.31054 45.07452 19.92057 49.94871 42.05699 45.69919 40.55247
#> [183] 28.77050 34.25098 39.57524 27.14581 44.69057 36.14965 49.50564
#> [190] 49.79043 17.99559 39.65697 44.97010 18.31935 31.24522 31.07475
#> [197] 21.61906 40.06484 34.99030 21.94425 37.44403 40.21178 38.23743
#> [204] 31.80890 34.61897 47.81524 34.58307 30.49509 45.29616 49.07757
#> [211] 24.17640 35.64875 17.63070 21.61867 32.29813 26.41488 28.31542
#> [218] 25.02318 20.23520 28.13247 63.69313 42.52417 29.03129 54.03181
#> [225] 25.60167 66.22389 26.02854 43.94607 39.26708 21.90635 33.10292
#> [232] 31.36953 68.74632 49.57971 36.77692 62.23430 33.17239 34.70213
#> [239] 29.33086 40.40664 20.51693 56.48982 47.57652 18.78920 39.83695
#> [246] 23.57444 32.90584 23.97282 29.16350 33.94278 33.32760 40.39087
#> [253] 37.08789 34.55488 28.07540 34.55889 32.50873 30.26050 31.61021
#> [260] 29.22609 21.66017 39.99861 31.54268 54.66244 28.83481 50.43102
#> [267] 41.57023 36.52691 41.74322 29.88869 65.63664 28.92781 31.62743
#> [274] 60.02248 23.41874 30.41566 49.28914 30.75073 41.08489 35.95343
#> [281] 26.30653 30.42233 35.58619 27.11696 41.07739 32.16801 54.22658
#> [288] 30.58481 32.75808 40.14170 38.59850 34.62828 26.92407 32.65613
#> [295] 21.12857 21.76199 31.72514 32.81883 39.57492 29.56246 26.52171
#> [302] 33.16808 30.46846 26.71148 20.12177 28.85316 25.85809 73.07025
#> [309] 50.11722 55.60337 42.62562 53.62811 40.37492 36.09093 54.15097
#> [316] 52.48111 28.21508 44.33563 15.14660 31.77283 28.02836 42.85488
#> [323] 30.07936 32.42728 33.91356 17.04858 29.01530 31.04799 24.28621
#> [330] 35.50456 45.96182 21.99371 38.45540 25.78633 45.07985 27.04933
#> [337] 50.03548 29.92024 26.27057 24.47919 59.13347 35.87683 42.14550
#> [344] 29.36456 44.58931 30.97851 21.83860 46.47922 39.71751 20.74531
#> [351] 21.96494 27.95186 40.64999 65.79466 34.95445 33.87721 27.41981
#> [358] 19.67562 39.39982 45.69528 22.18879 37.54553 23.15847 28.45508
#> [365] 25.23477 33.00227 27.16574 34.19212 38.82416 17.26278 38.40626
#> [372] 57.01508 40.28032 27.15082 32.21021 41.59108 44.75365 31.57659
#> [379] 44.49800 41.11233 35.23455 24.47634 45.13415 37.24519 42.85021
#> [386] 32.84645 37.01077 38.96790 40.08106 43.99265 32.24746 27.24075
#> [393] 31.66613 34.98403 27.29397 34.99001 31.25752 30.07230 27.18477
#> [400] 37.36462 34.40921 27.16085 37.36703 47.98335 43.48091 23.31231
#> [407] 20.68531 40.72063 13.66989 27.99689 25.61063 27.89089 17.93238
#> [414] 23.25505 69.87353 20.53952 38.76444 45.53784 43.99368 25.86236
#> [421] 23.02465 26.68788 51.99475 31.49945 39.98303 25.96329 18.68290
#> [428] 45.39740 41.85522 40.88774 33.13019 36.51401 43.93668 28.72223
#> [435] 17.36850 29.80030 29.36764 33.21636 30.98314 44.00905 49.96474
#> [442] 32.63317 34.95938 42.09920 25.98961 26.13540 40.91752 27.13926
#> [449] 23.93415 44.34438 24.80069 39.56627 34.17161 29.33848 51.51685
#> [456] 38.10154 17.89906 29.84155 20.73680 17.94649 20.14526 30.60828
#> [463] 37.05229 26.99159 48.47064 29.63704 30.29811 29.44919 50.20743
#> [470] 25.22852 19.31610 49.49408 31.13921 45.04409 26.36500 21.37141
#> [477] 33.60464 39.82629 23.44417 50.85233 35.55273 31.42400 52.78349
#> [484] 46.42078 32.84158 41.58214 37.57874 92.79539 21.87917 35.86701
#> [491] 44.63170 23.67373 49.57926 37.82632 28.51937 54.19448 25.42921
#> [498] 31.42047 45.75800 26.14005 32.43037 30.31998 60.34780 35.38384
#> [505] 17.65934 49.95322 48.97623 24.37608 62.05997 17.90258 35.04199
#> [512] 25.02686 37.13100 27.42116 46.56513 14.44667 18.13457 30.41839
#> [519] 40.06058 33.26711 58.99535 23.18483 36.67044 24.95331 27.19064
#> [526] 26.76947 37.48431 37.13503 22.80870 32.98376 16.45626 25.22453
#> [533] 35.59700 24.01433 58.24541 34.09432 31.09085 29.28524 20.65437
#> [540] 24.52000 61.00638 33.59970 19.62836 30.89483 27.49646 47.74031
#> [547] 38.48854 79.28284 49.83587 41.20827 60.84168 58.74430 73.74234
#> [554] 62.99021 44.73661 66.14946 78.63431 58.85001 56.29965 49.76806
#> [561] 66.31184 77.24626 30.20323 34.36305 40.14230 115.76308 53.35118
#> [568] 56.61291 54.02821 30.86656 64.91494 51.47610 58.02405 46.19877
#> [575] 75.46288 62.38693 62.12430 29.65914 48.83256 48.45711 87.84555
#> [582] 48.89591 79.45862 45.43495 61.17216 44.15376 40.81283 28.66775
#> [589] 100.81542 80.80345 59.82787 60.46746 61.44131 33.23726 52.19624
#> [596] 83.51128 53.55938 63.91426 43.91224 55.36213 54.68760 56.36276
#> [603] 50.26803 63.36135 71.84053 44.01963 54.90876 48.05082 73.33604
#> [610] 40.86609 53.14413 59.74683 74.13609 72.72819 73.80368 46.35780
#> [617] 39.46049 69.37131 69.23278 39.48316 65.63175 50.51306 79.59284
#> [624] 43.27989 29.25963 53.94132 47.30325 89.88726 64.49022 53.12747
#> [631] 51.61317 47.72412 102.46424 79.80996 51.62739 45.94677 44.20380
#> [638] 62.47154 56.71323 45.20940 33.56516 93.76083 56.27748 43.03061
#> [645] 86.12136 66.81985 103.73717 45.81972 66.39085 43.21773 56.16747
#> [652] 59.28413 50.73493 65.26301 107.46498 68.39817 77.53655 63.00234
#> [659] 100.37694 50.08347 51.31859 47.84582 73.28803 56.60291 49.47953
#> [666] 74.14721 51.88331 72.97605 37.36928 50.55296 94.49818 85.63369
#> [673] 47.21940 51.29463 30.87699 40.99069 65.22233 84.18339 36.97547
#> [680] 67.67693 130.27515 56.50564 52.08214 36.62894 50.17403 43.98132
#> [687] 63.78818 69.71901 58.66280 34.25625 40.01212 38.51369 31.93027
#> [694] 70.08009 60.78508 51.19670 65.45439 70.13630 38.38639 46.42615
#> [701] 59.55314 49.09690 60.75484 66.66783 70.41840 77.79466 57.57120
#> [708] 66.27876 40.41878 51.19402 90.55426 28.21335 67.71025 52.72485
#> [715] 37.34428 72.43783 92.29608 55.59297 69.66448 58.30077 50.26778
#> [722] 74.61613 50.92561 51.97960 99.50324 47.12665 87.80435 119.15289
#> [729] 96.67512 27.20912 42.35955 51.36019 66.15466 50.99965 31.33727
#> [736] 29.62981 55.37496 72.04834 44.82771 46.57539 64.62869 38.82131
#> [743] 53.86127 30.62108 27.37893 85.39840 55.85290 64.89730 94.68730
#> [750] 35.15146 37.51919 45.72001 89.69830 46.13428 66.35095 37.41977
#> [757] 43.10677 40.13555 43.13188 24.73451 76.52571 36.36566 71.17790
#> [764] 56.44084 63.19831 38.86127 56.54947 83.05808 41.66112 60.14119
#> [771] 73.36839 36.83335 46.99687 68.72470 48.02621 37.04922 67.67630
#> [778] 46.78206 43.38829 79.76107 43.42811 34.89142 46.70848 85.92108
#> [785] 65.54841 39.49996 41.09837 47.97916 62.31907 75.42977 83.27070
#> [792] 73.13176 58.56810 75.03824 37.08341 57.11212 62.88590 80.01578
#> [799] 31.43220 50.27634 20.52318 57.18749 65.93147 42.64495 60.78448
#> [806] 42.12619 44.69412 58.64844 68.76875 163.36185 59.30573 44.16434
#> [813] 74.02857 42.16594 47.80402 46.06946 68.13544 58.27459 44.44837
#> [820] 49.71347 41.92370 65.10552 190.42879 100.55114 84.73240 95.19440
#> [827] 62.62765 81.34105 62.84927 119.41128 97.69586 103.24047 132.04779
#> [834] 63.94897 61.11686 68.83021 80.70128 118.36174 69.88491 75.67939
#> [841] 97.87433 84.47204 167.57416 119.33953 112.87803 94.60966 54.52644
#> [848] 134.89541 80.76840 100.86500 125.36064 80.85360 81.27602 102.14881
#> [855] 62.87013 89.81105 90.54166 77.87923 154.26053 104.44530 89.99370
#> [862] 137.11783 108.63313 81.65888 91.76187 153.53548 93.17887 131.28943
#> [869] 58.95745 63.59264 86.73104 159.01308 56.48464 53.76414 79.36095
#> [876] 104.17268 82.69108 75.47191 80.10494 123.34176 117.11018 82.67987
#> [883] 87.24288 77.92377 105.19438 75.47461 73.26672 103.96131 88.69445
#> [890] 67.40834 115.24510 107.64339 93.11673 129.87959 126.03289 118.21727
#> [897] 101.24318 85.84310 83.24171 94.37437 95.52714 58.18705 70.93290
#> [904] 135.64519 122.17646 47.94730 81.90610 71.29312 59.56557 90.96883
#> [911] 105.27981 68.10784 62.24482 118.12494 89.29744 104.93346 54.31292
#> [918] 118.22755 85.99992 68.28882 116.87775 59.89081 88.51994 124.96078
#> [925] 48.99528 83.42296 39.21350 104.91602 96.76956 112.59752 71.12703
#> [932] 88.73937 68.98548 70.70640 93.68761 131.72255 82.59086 81.56980
#> [939] 80.12171 160.72231 130.68852 61.65840 175.64769 103.14938 133.32521
#> [946] 160.15746 97.61800 119.62046 125.04584 120.67301 110.96952 62.16252
#> [953] 215.10540 81.98616 110.52191 53.11782 83.00635 59.01162 167.43096
#> [960] 146.43115 136.73301 93.53995 92.63548 98.56852 59.88143 101.45146
#> [967] 102.84065 115.38549 110.87331 96.65850 70.26512 73.19904 204.44288
#> [974] 120.52524 148.47584 176.52242 72.50633 98.01507 85.07589 122.09749
#> [981] 173.47087 272.06243 114.84247 194.43547 182.95500 99.70758 155.32184
#> [988] 234.90205 149.08372 129.43951 92.17400 150.30666 127.34289 95.56536
#> [995] 183.85856 173.20963 119.36203 298.97556 239.90785 149.72990 145.83624
#> [1002] 199.97769 221.71715 124.50443 127.57657 126.63670 224.84161 193.52027
#> [1009] 67.17684 193.24399 163.77183 115.04808 139.80491 194.08049 142.56183
#> [1016] 150.05278 112.32713 229.27074 123.95988 146.80726 185.69923 111.44768
#> [1023] 148.97687 122.53709 127.37003 92.55487 106.25934 151.61132 166.55049
#> [1030] 166.27216 89.84812 285.64838 210.83361 119.86280 120.26534 166.67314
#> [1037] 128.77576 128.26908 203.90985 124.66021 285.09853 111.19870 185.07644
#> [1044] 88.79945 97.17543 121.60783 183.18550 113.42228 234.66441 148.81920
#> [1051] 127.67544 144.30028 183.15017 180.80073 212.84778 81.80066 156.28369
#> [1058] 217.85070 136.70053 196.65904 155.49179 120.33784 123.21350 293.16047
#> [1065] 141.29326 286.30265 137.11341 191.99534 155.88733 232.83108 141.37831
#> [1072] 114.62536 154.08698 129.56200 197.71852 143.31929 155.63173 166.92790
#> [1079] 151.48311 133.67364 183.79864 134.72402 108.41123 113.01052 145.28928
#> [1086] 85.79995 220.96699 127.18015 215.14311 190.93505 156.44133 164.06449
#> [1093] 164.81190 85.39927 179.14410 135.09159
changepoints(seg)
#> [1] 330 839
fitness(seg)
#> BIC
#> 10554.84