Nothing
tests/testthat/_snaps/qts-prcomp.md
In squat: Statistics for Quaternion Temporal Data
The function prcomp() works for QTS samples
Code
res_pca
Output
$x
[[1]]
# A tibble: 101 x 5
time w x y z
<int> <dec:.5!> <dec:.5!> <dec:.5!> <dec:.5!>
1 0 0.99427 0.07973 0.06988 0.01334
2 1 0.99483 0.07457 0.06763 0.01313
3 2 0.99542 0.06931 0.06457 0.01269
4 3 0.99602 0.06398 0.06091 0.01184
5 4 0.99652 0.05949 0.05742 0.01070
6 5 0.99694 0.05572 0.05403 0.00932
7 6 0.99729 0.05275 0.05079 0.00772
8 7 0.99757 0.05056 0.04761 0.00583
9 8 0.99782 0.04883 0.04430 0.00366
10 9 0.99805 0.04730 0.04071 0.00125
# i 91 more rows
[[2]]
# A tibble: 101 x 5
time w x y z
<int> <dec:.5!> <dec:.5!> <dec:.5!> <dec:.5!>
1 0 0.99379 0.08282 0.07370 0.00994
2 1 0.99441 0.07727 0.07120 0.01036
3 2 0.99503 0.07171 0.06829 0.01059
4 3 0.99565 0.06598 0.06489 0.01047
5 4 0.99625 0.06032 0.06124 0.01005
6 5 0.99677 0.05525 0.05756 0.00927
7 6 0.99717 0.05142 0.05417 0.00810
8 7 0.99751 0.04849 0.05080 0.00655
9 8 0.99780 0.04622 0.04723 0.00461
10 9 0.99806 0.04442 0.04345 0.00237
# i 91 more rows
[[3]]
# A tibble: 101 x 5
time w x y z
<int> <dec:.5!> <dec:.5!> <dec:.5!> <dec:.5!>
1 0 0.99262 0.09948 0.06271 -0.02971
2 1 0.99312 0.09388 0.06347 -0.02941
3 2 0.99375 0.08743 0.06335 -0.02831
4 3 0.99446 0.08006 0.06255 -0.02696
5 4 0.99511 0.07312 0.06135 -0.02551
6 5 0.99566 0.06703 0.05977 -0.02423
7 6 0.99614 0.06183 0.05782 -0.02305
8 7 0.99656 0.05763 0.05543 -0.02198
9 8 0.99692 0.05426 0.05257 -0.02103
10 9 0.99726 0.05151 0.04915 -0.02020
# i 91 more rows
[[4]]
# A tibble: 101 x 5
time w x y z
<int> <dec:.5!> <dec:.5!> <dec:.5!> <dec:.5!>
1 0 0.99281 0.09669 0.06308 -0.03165
2 1 0.99331 0.09099 0.06403 -0.03082
3 2 0.99390 0.08485 0.06391 -0.02969
4 3 0.99452 0.07821 0.06324 -0.02837
5 4 0.99514 0.07160 0.06207 -0.02695
6 5 0.99567 0.06570 0.06052 -0.02564
7 6 0.99613 0.06075 0.05862 -0.02447
8 7 0.99651 0.05693 0.05633 -0.02347
9 8 0.99685 0.05402 0.05358 -0.02258
10 9 0.99716 0.05187 0.05014 -0.02182
# i 91 more rows
[[5]]
# A tibble: 101 x 5
time w x y z
<int> <dec:.5!> <dec:.5!> <dec:.5!> <dec:.5!>
1 0 0.99414 0.08053 0.07026 0.01615
2 1 0.99469 0.07558 0.06822 0.01535
3 2 0.99521 0.07085 0.06566 0.01506
4 3 0.99574 0.06628 0.06246 0.01461
5 4 0.99623 0.06202 0.05899 0.01379
6 5 0.99669 0.05810 0.05541 0.01259
7 6 0.99710 0.05466 0.05184 0.01102
8 7 0.99743 0.05196 0.04844 0.00912
9 8 0.99771 0.04994 0.04508 0.00691
10 9 0.99795 0.04836 0.04157 0.00448
# i 91 more rows
[[6]]
# A tibble: 101 x 5
time w x y z
<int> <dec:.5!> <dec:.5!> <dec:.5!> <dec:.5!>
1 0 0.99326 0.08804 0.07386 0.01483
2 1 0.99376 0.08244 0.07368 0.01449
3 2 0.99434 0.07693 0.07184 0.01450
4 3 0.99498 0.07123 0.06879 0.01445
5 4 0.99561 0.06567 0.06516 0.01412
6 5 0.99617 0.06071 0.06152 0.01353
7 6 0.99664 0.05649 0.05800 0.01258
8 7 0.99700 0.05351 0.05475 0.01112
9 8 0.99730 0.05149 0.05157 0.00922
10 9 0.99757 0.04996 0.04815 0.00687
# i 91 more rows
[[7]]
# A tibble: 101 x 5
time w x y z
<int> <dec:.5!> <dec:.5!> <dec:.5!> <dec:.5!>
1 0 0.99544 0.07361 0.03614 -0.04869
2 1 0.99563 0.07000 0.03835 -0.04843
3 2 0.99579 0.06682 0.04066 -0.04779
4 3 0.99597 0.06369 0.04263 -0.04663
5 4 0.99617 0.06045 0.04409 -0.04516
6 5 0.99640 0.05724 0.04502 -0.04345
7 6 0.99663 0.05414 0.04557 -0.04139
8 7 0.99688 0.05142 0.04526 -0.03931
9 8 0.99712 0.04916 0.04413 -0.03727
10 9 0.99736 0.04716 0.04244 -0.03530
# i 91 more rows
[[8]]
# A tibble: 101 x 5
time w x y z
<int> <dec:.5!> <dec:.5!> <dec:.5!> <dec:.5!>
1 0 0.99506 0.06909 0.04686 -0.05375
2 1 0.99525 0.06662 0.04888 -0.05157
3 2 0.99547 0.06355 0.05103 -0.04893
4 3 0.99572 0.06026 0.05258 -0.04627
5 4 0.99599 0.05693 0.05343 -0.04370
6 5 0.99627 0.05376 0.05346 -0.04124
7 6 0.99656 0.05103 0.05246 -0.03897
8 7 0.99685 0.04876 0.05047 -0.03688
9 8 0.99715 0.04701 0.04758 -0.03491
10 9 0.99745 0.04557 0.04389 -0.03303
# i 91 more rows
[[9]]
# A tibble: 101 x 5
time w x y z
<int> <dec:.5!> <dec:.5!> <dec:.5!> <dec:.5!>
1 0 0.99416 0.08373 0.06392 0.02332
2 1 0.99469 0.07722 0.06345 0.02448
3 2 0.99533 0.06977 0.06172 0.02525
4 3 0.99605 0.06144 0.05870 0.02562
5 4 0.99673 0.05348 0.05494 0.02533
6 5 0.99733 0.04646 0.05084 0.02434
7 6 0.99780 0.04115 0.04679 0.02247
8 7 0.99816 0.03771 0.04320 0.01981
9 8 0.99842 0.03582 0.04020 0.01636
10 9 0.99859 0.03487 0.03794 0.01247
# i 91 more rows
[[10]]
# A tibble: 101 x 5
time w x y z
<int> <dec:.5!> <dec:.5!> <dec:.5!> <dec:.5!>
1 0 0.99410 0.08159 0.06763 0.02292
2 1 0.99466 0.07394 0.06792 0.02377
3 2 0.99529 0.06609 0.06654 0.02472
4 3 0.99595 0.05819 0.06373 0.02520
5 4 0.99660 0.05040 0.06008 0.02510
6 5 0.99718 0.04344 0.05611 0.02428
7 6 0.99766 0.03784 0.05219 0.02265
8 7 0.99802 0.03411 0.04873 0.02029
9 8 0.99829 0.03204 0.04579 0.01737
10 9 0.99846 0.03142 0.04348 0.01395
# i 91 more rows
[[11]]
# A tibble: 101 x 5
time w x y z
<int> <dec:.5!> <dec:.5!> <dec:.5!> <dec:.5!>
1 0 0.99378 0.09127 0.06209 0.01488
2 1 0.99427 0.08384 0.06456 0.01546
3 2 0.99474 0.07662 0.06608 0.01613
4 3 0.99520 0.07008 0.06629 0.01666
5 4 0.99560 0.06501 0.06528 0.01686
6 5 0.99600 0.06116 0.06301 0.01667
7 6 0.99642 0.05817 0.05930 0.01604
8 7 0.99687 0.05533 0.05442 0.01509
9 8 0.99731 0.05265 0.04899 0.01382
10 9 0.99771 0.05023 0.04370 0.01222
# i 91 more rows
[[12]]
# A tibble: 101 x 5
time w x y z
<int> <dec:.5!> <dec:.5!> <dec:.5!> <dec:.5!>
1 0 0.99378 0.09099 0.06243 0.01470
2 1 0.99423 0.08331 0.06576 0.01532
3 2 0.99467 0.07589 0.06787 0.01635
4 3 0.99510 0.06927 0.06838 0.01739
5 4 0.99556 0.06364 0.06695 0.01831
6 5 0.99606 0.05855 0.06378 0.01903
7 6 0.99659 0.05407 0.05925 0.01932
8 7 0.99710 0.05016 0.05397 0.01914
9 8 0.99753 0.04716 0.04864 0.01831
10 9 0.99786 0.04505 0.04430 0.01688
# i 91 more rows
[[13]]
# A tibble: 101 x 5
time w x y z
<int> <dec:.5!> <dec:.5!> <dec:.5!> <dec:.5!>
1 0 0.99572 0.05082 0.07120 0.02989
2 1 0.99607 0.04731 0.06851 0.03020
3 2 0.99652 0.04346 0.06424 0.03059
4 3 0.99690 0.04018 0.06048 0.03024
5 4 0.99721 0.03769 0.05743 0.02918
6 5 0.99745 0.03611 0.05520 0.02739
7 6 0.99762 0.03522 0.05363 0.02507
8 7 0.99777 0.03469 0.05249 0.02237
9 8 0.99790 0.03413 0.05149 0.01936
10 9 0.99805 0.03312 0.05041 0.01624
# i 91 more rows
[[14]]
# A tibble: 101 x 5
time w x y z
<int> <dec:.5!> <dec:.5!> <dec:.5!> <dec:.5!>
1 0 0.99533 0.05730 0.07186 0.02939
2 1 0.99564 0.05383 0.06994 0.03028
3 2 0.99602 0.04977 0.06725 0.03076
4 3 0.99642 0.04603 0.06398 0.03065
5 4 0.99679 0.04294 0.06059 0.02990
6 5 0.99711 0.04071 0.05741 0.02849
7 6 0.99739 0.03935 0.05452 0.02648
8 7 0.99761 0.03863 0.05191 0.02407
9 8 0.99782 0.03810 0.04948 0.02144
10 9 0.99802 0.03731 0.04712 0.01868
# i 91 more rows
[[15]]
# A tibble: 101 x 5
time w x y z
<int> <dec:.5!> <dec:.5!> <dec:.5!> <dec:.5!>
1 0 0.99572 0.04763 0.07857 0.00966
2 1 0.99606 0.04320 0.07662 0.01099
3 2 0.99645 0.03916 0.07353 0.01212
4 3 0.99685 0.03575 0.06964 0.01263
5 4 0.99723 0.03312 0.06537 0.01245
6 5 0.99757 0.03146 0.06115 0.01154
7 6 0.99784 0.03067 0.05716 0.00996
8 7 0.99807 0.03046 0.05351 0.00791
9 8 0.99826 0.03047 0.05026 0.00564
10 9 0.99841 0.03027 0.04742 0.00342
# i 91 more rows
[[16]]
# A tibble: 101 x 5
time w x y z
<int> <dec:.5!> <dec:.5!> <dec:.5!> <dec:.5!>
1 0 0.99508 0.05950 0.07884 0.00834
2 1 0.99543 0.05417 0.07795 0.00998
3 2 0.99583 0.04959 0.07573 0.01138
4 3 0.99625 0.04556 0.07256 0.01228
5 4 0.99665 0.04230 0.06889 0.01263
6 5 0.99701 0.03996 0.06501 0.01235
7 6 0.99731 0.03857 0.06124 0.01144
8 7 0.99757 0.03784 0.05758 0.00995
9 8 0.99781 0.03740 0.05400 0.00803
10 9 0.99803 0.03681 0.05039 0.00590
# i 91 more rows
attr(,"class")
[1] "qts_sample" "list"
$tpca
5 multivariate functional principal components estimated with 3 elements, each.
* * * * * * * * * *
Eigenvalues:
[1] 0.025494786 0.009011399 0.004626775 0.002175458 0.001022167
$var_props
[1] 0.47252278 0.16701812 0.08575308 0.04032015 0.01894495
$total_variance
[1] 0.05395462
$mean_qts
# A tibble: 101 x 5
time w x y z
<int> <dec:.5!> <dec:.5!> <dec:.5!> <dec:.5!>
1 0 0.99484 0.07709 0.06585 0.00272
2 1 0.99525 0.07180 0.06567 0.00335
3 2 0.99570 0.06639 0.06455 0.00409
4 3 0.99616 0.06104 0.06264 0.00461
5 4 0.99659 0.05616 0.06023 0.00482
6 5 0.99698 0.05198 0.05751 0.00464
7 6 0.99731 0.04865 0.05460 0.00406
8 7 0.99760 0.04615 0.05157 0.00310
9 8 0.99784 0.04430 0.04844 0.00181
10 9 0.99806 0.04283 0.04527 0.00027
# i 91 more rows
$principal_qts
$principal_qts[[1]]
# A tibble: 101 x 5
time w x y z
<int> <dec:.5!> <dec:.5!> <dec:.5!> <dec:.5!>
1 0 0.98157 0.03639 0.07900 0.17017
2 1 0.98271 0.03195 0.07968 0.16406
3 2 0.98386 0.02726 0.07949 0.15798
4 3 0.98506 0.02253 0.07856 0.15162
5 4 0.98627 0.01824 0.07710 0.14489
6 5 0.98749 0.01465 0.07529 0.13776
7 6 0.98870 0.01193 0.07322 0.13023
8 7 0.98990 0.01009 0.07098 0.12233
9 8 0.99106 0.00894 0.06860 0.11410
10 9 0.99216 0.00823 0.06619 0.10565
# i 91 more rows
$principal_qts[[2]]
# A tibble: 101 x 5
time w x y z
<int> <dec:.5!> <dec:.5!> <dec:.5!> <dec:.5!>
1 0 0.98215 0.18227 0.03969 0.02418
2 1 0.98344 0.17493 0.04083 0.02421
3 2 0.98473 0.16736 0.04130 0.02424
4 3 0.98601 0.15972 0.04120 0.02393
5 4 0.98720 0.15243 0.04079 0.02314
6 5 0.98826 0.14574 0.04022 0.02178
7 6 0.98919 0.13981 0.03962 0.01984
8 7 0.98997 0.13463 0.03903 0.01734
9 8 0.99066 0.13003 0.03849 0.01434
10 9 0.99127 0.12575 0.03805 0.01093
# i 91 more rows
$principal_qts[[3]]
# A tibble: 101 x 5
time w x y z
<int> <dec:.5!> <dec:.5!> <dec:.5!> <dec:.5!>
1 0 0.99958 0.00594 0.00842 -0.02710
2 1 0.99959 0.00912 0.01582 -0.02186
3 2 0.99955 0.01158 0.02220 -0.01668
4 3 0.99945 0.01348 0.02772 -0.01187
5 4 0.99932 0.01524 0.03266 -0.00752
6 5 0.99915 0.01711 0.03720 -0.00369
7 6 0.99895 0.01927 0.04145 -0.00036
8 7 0.99873 0.02173 0.04543 0.00248
9 8 0.99848 0.02432 0.04917 0.00491
10 9 0.99823 0.02681 0.05271 0.00701
# i 91 more rows
$principal_qts[[4]]
# A tibble: 101 x 5
time w x y z
<int> <dec:.5!> <dec:.5!> <dec:.5!> <dec:.5!>
1 0 0.99862 0.04023 -0.03290 -0.00762
2 1 0.99899 0.03564 -0.02557 -0.00963
3 2 0.99925 0.03140 -0.01945 -0.01141
4 3 0.99943 0.02764 -0.01435 -0.01329
5 4 0.99953 0.02475 -0.00999 -0.01538
6 5 0.99956 0.02293 -0.00615 -0.01776
7 6 0.99954 0.02234 -0.00269 -0.02042
8 7 0.99947 0.02292 0.00044 -0.02332
9 8 0.99935 0.02448 0.00327 -0.02640
10 9 0.99919 0.02675 0.00586 -0.02953
# i 91 more rows
$principal_qts[[5]]
# A tibble: 101 x 5
time w x y z
<int> <dec:.5!> <dec:.5!> <dec:.5!> <dec:.5!>
1 0 0.99416 0.09096 -0.04161 -0.04039
2 1 0.99603 0.07442 -0.02340 -0.04290
3 2 0.99724 0.05847 -0.00731 -0.04514
4 3 0.99791 0.04327 0.00686 -0.04746
5 4 0.99813 0.02922 0.01945 -0.04998
6 5 0.99800 0.01657 0.03071 -0.05276
7 6 0.99759 0.00546 0.04085 -0.05576
8 7 0.99700 -0.00413 0.04995 -0.05894
9 8 0.99629 -0.01238 0.05808 -0.06221
10 9 0.99552 -0.01959 0.06532 -0.06545
# i 91 more rows
attr(,"class")
[1] "prcomp_qts"
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The function prcomp() works for QTS samples
Code
res_pca
Output
$x
[[1]]
# A tibble: 101 x 5
time w x y z
<int> <dec:.5!> <dec:.5!> <dec:.5!> <dec:.5!>
1 0 0.99427 0.07973 0.06988 0.01334
2 1 0.99483 0.07457 0.06763 0.01313
3 2 0.99542 0.06931 0.06457 0.01269
4 3 0.99602 0.06398 0.06091 0.01184
5 4 0.99652 0.05949 0.05742 0.01070
6 5 0.99694 0.05572 0.05403 0.00932
7 6 0.99729 0.05275 0.05079 0.00772
8 7 0.99757 0.05056 0.04761 0.00583
9 8 0.99782 0.04883 0.04430 0.00366
10 9 0.99805 0.04730 0.04071 0.00125
# i 91 more rows
[[2]]
# A tibble: 101 x 5
time w x y z
<int> <dec:.5!> <dec:.5!> <dec:.5!> <dec:.5!>
1 0 0.99379 0.08282 0.07370 0.00994
2 1 0.99441 0.07727 0.07120 0.01036
3 2 0.99503 0.07171 0.06829 0.01059
4 3 0.99565 0.06598 0.06489 0.01047
5 4 0.99625 0.06032 0.06124 0.01005
6 5 0.99677 0.05525 0.05756 0.00927
7 6 0.99717 0.05142 0.05417 0.00810
8 7 0.99751 0.04849 0.05080 0.00655
9 8 0.99780 0.04622 0.04723 0.00461
10 9 0.99806 0.04442 0.04345 0.00237
# i 91 more rows
[[3]]
# A tibble: 101 x 5
time w x y z
<int> <dec:.5!> <dec:.5!> <dec:.5!> <dec:.5!>
1 0 0.99262 0.09948 0.06271 -0.02971
2 1 0.99312 0.09388 0.06347 -0.02941
3 2 0.99375 0.08743 0.06335 -0.02831
4 3 0.99446 0.08006 0.06255 -0.02696
5 4 0.99511 0.07312 0.06135 -0.02551
6 5 0.99566 0.06703 0.05977 -0.02423
7 6 0.99614 0.06183 0.05782 -0.02305
8 7 0.99656 0.05763 0.05543 -0.02198
9 8 0.99692 0.05426 0.05257 -0.02103
10 9 0.99726 0.05151 0.04915 -0.02020
# i 91 more rows
[[4]]
# A tibble: 101 x 5
time w x y z
<int> <dec:.5!> <dec:.5!> <dec:.5!> <dec:.5!>
1 0 0.99281 0.09669 0.06308 -0.03165
2 1 0.99331 0.09099 0.06403 -0.03082
3 2 0.99390 0.08485 0.06391 -0.02969
4 3 0.99452 0.07821 0.06324 -0.02837
5 4 0.99514 0.07160 0.06207 -0.02695
6 5 0.99567 0.06570 0.06052 -0.02564
7 6 0.99613 0.06075 0.05862 -0.02447
8 7 0.99651 0.05693 0.05633 -0.02347
9 8 0.99685 0.05402 0.05358 -0.02258
10 9 0.99716 0.05187 0.05014 -0.02182
# i 91 more rows
[[5]]
# A tibble: 101 x 5
time w x y z
<int> <dec:.5!> <dec:.5!> <dec:.5!> <dec:.5!>
1 0 0.99414 0.08053 0.07026 0.01615
2 1 0.99469 0.07558 0.06822 0.01535
3 2 0.99521 0.07085 0.06566 0.01506
4 3 0.99574 0.06628 0.06246 0.01461
5 4 0.99623 0.06202 0.05899 0.01379
6 5 0.99669 0.05810 0.05541 0.01259
7 6 0.99710 0.05466 0.05184 0.01102
8 7 0.99743 0.05196 0.04844 0.00912
9 8 0.99771 0.04994 0.04508 0.00691
10 9 0.99795 0.04836 0.04157 0.00448
# i 91 more rows
[[6]]
# A tibble: 101 x 5
time w x y z
<int> <dec:.5!> <dec:.5!> <dec:.5!> <dec:.5!>
1 0 0.99326 0.08804 0.07386 0.01483
2 1 0.99376 0.08244 0.07368 0.01449
3 2 0.99434 0.07693 0.07184 0.01450
4 3 0.99498 0.07123 0.06879 0.01445
5 4 0.99561 0.06567 0.06516 0.01412
6 5 0.99617 0.06071 0.06152 0.01353
7 6 0.99664 0.05649 0.05800 0.01258
8 7 0.99700 0.05351 0.05475 0.01112
9 8 0.99730 0.05149 0.05157 0.00922
10 9 0.99757 0.04996 0.04815 0.00687
# i 91 more rows
[[7]]
# A tibble: 101 x 5
time w x y z
<int> <dec:.5!> <dec:.5!> <dec:.5!> <dec:.5!>
1 0 0.99544 0.07361 0.03614 -0.04869
2 1 0.99563 0.07000 0.03835 -0.04843
3 2 0.99579 0.06682 0.04066 -0.04779
4 3 0.99597 0.06369 0.04263 -0.04663
5 4 0.99617 0.06045 0.04409 -0.04516
6 5 0.99640 0.05724 0.04502 -0.04345
7 6 0.99663 0.05414 0.04557 -0.04139
8 7 0.99688 0.05142 0.04526 -0.03931
9 8 0.99712 0.04916 0.04413 -0.03727
10 9 0.99736 0.04716 0.04244 -0.03530
# i 91 more rows
[[8]]
# A tibble: 101 x 5
time w x y z
<int> <dec:.5!> <dec:.5!> <dec:.5!> <dec:.5!>
1 0 0.99506 0.06909 0.04686 -0.05375
2 1 0.99525 0.06662 0.04888 -0.05157
3 2 0.99547 0.06355 0.05103 -0.04893
4 3 0.99572 0.06026 0.05258 -0.04627
5 4 0.99599 0.05693 0.05343 -0.04370
6 5 0.99627 0.05376 0.05346 -0.04124
7 6 0.99656 0.05103 0.05246 -0.03897
8 7 0.99685 0.04876 0.05047 -0.03688
9 8 0.99715 0.04701 0.04758 -0.03491
10 9 0.99745 0.04557 0.04389 -0.03303
# i 91 more rows
[[9]]
# A tibble: 101 x 5
time w x y z
<int> <dec:.5!> <dec:.5!> <dec:.5!> <dec:.5!>
1 0 0.99416 0.08373 0.06392 0.02332
2 1 0.99469 0.07722 0.06345 0.02448
3 2 0.99533 0.06977 0.06172 0.02525
4 3 0.99605 0.06144 0.05870 0.02562
5 4 0.99673 0.05348 0.05494 0.02533
6 5 0.99733 0.04646 0.05084 0.02434
7 6 0.99780 0.04115 0.04679 0.02247
8 7 0.99816 0.03771 0.04320 0.01981
9 8 0.99842 0.03582 0.04020 0.01636
10 9 0.99859 0.03487 0.03794 0.01247
# i 91 more rows
[[10]]
# A tibble: 101 x 5
time w x y z
<int> <dec:.5!> <dec:.5!> <dec:.5!> <dec:.5!>
1 0 0.99410 0.08159 0.06763 0.02292
2 1 0.99466 0.07394 0.06792 0.02377
3 2 0.99529 0.06609 0.06654 0.02472
4 3 0.99595 0.05819 0.06373 0.02520
5 4 0.99660 0.05040 0.06008 0.02510
6 5 0.99718 0.04344 0.05611 0.02428
7 6 0.99766 0.03784 0.05219 0.02265
8 7 0.99802 0.03411 0.04873 0.02029
9 8 0.99829 0.03204 0.04579 0.01737
10 9 0.99846 0.03142 0.04348 0.01395
# i 91 more rows
[[11]]
# A tibble: 101 x 5
time w x y z
<int> <dec:.5!> <dec:.5!> <dec:.5!> <dec:.5!>
1 0 0.99378 0.09127 0.06209 0.01488
2 1 0.99427 0.08384 0.06456 0.01546
3 2 0.99474 0.07662 0.06608 0.01613
4 3 0.99520 0.07008 0.06629 0.01666
5 4 0.99560 0.06501 0.06528 0.01686
6 5 0.99600 0.06116 0.06301 0.01667
7 6 0.99642 0.05817 0.05930 0.01604
8 7 0.99687 0.05533 0.05442 0.01509
9 8 0.99731 0.05265 0.04899 0.01382
10 9 0.99771 0.05023 0.04370 0.01222
# i 91 more rows
[[12]]
# A tibble: 101 x 5
time w x y z
<int> <dec:.5!> <dec:.5!> <dec:.5!> <dec:.5!>
1 0 0.99378 0.09099 0.06243 0.01470
2 1 0.99423 0.08331 0.06576 0.01532
3 2 0.99467 0.07589 0.06787 0.01635
4 3 0.99510 0.06927 0.06838 0.01739
5 4 0.99556 0.06364 0.06695 0.01831
6 5 0.99606 0.05855 0.06378 0.01903
7 6 0.99659 0.05407 0.05925 0.01932
8 7 0.99710 0.05016 0.05397 0.01914
9 8 0.99753 0.04716 0.04864 0.01831
10 9 0.99786 0.04505 0.04430 0.01688
# i 91 more rows
[[13]]
# A tibble: 101 x 5
time w x y z
<int> <dec:.5!> <dec:.5!> <dec:.5!> <dec:.5!>
1 0 0.99572 0.05082 0.07120 0.02989
2 1 0.99607 0.04731 0.06851 0.03020
3 2 0.99652 0.04346 0.06424 0.03059
4 3 0.99690 0.04018 0.06048 0.03024
5 4 0.99721 0.03769 0.05743 0.02918
6 5 0.99745 0.03611 0.05520 0.02739
7 6 0.99762 0.03522 0.05363 0.02507
8 7 0.99777 0.03469 0.05249 0.02237
9 8 0.99790 0.03413 0.05149 0.01936
10 9 0.99805 0.03312 0.05041 0.01624
# i 91 more rows
[[14]]
# A tibble: 101 x 5
time w x y z
<int> <dec:.5!> <dec:.5!> <dec:.5!> <dec:.5!>
1 0 0.99533 0.05730 0.07186 0.02939
2 1 0.99564 0.05383 0.06994 0.03028
3 2 0.99602 0.04977 0.06725 0.03076
4 3 0.99642 0.04603 0.06398 0.03065
5 4 0.99679 0.04294 0.06059 0.02990
6 5 0.99711 0.04071 0.05741 0.02849
7 6 0.99739 0.03935 0.05452 0.02648
8 7 0.99761 0.03863 0.05191 0.02407
9 8 0.99782 0.03810 0.04948 0.02144
10 9 0.99802 0.03731 0.04712 0.01868
# i 91 more rows
[[15]]
# A tibble: 101 x 5
time w x y z
<int> <dec:.5!> <dec:.5!> <dec:.5!> <dec:.5!>
1 0 0.99572 0.04763 0.07857 0.00966
2 1 0.99606 0.04320 0.07662 0.01099
3 2 0.99645 0.03916 0.07353 0.01212
4 3 0.99685 0.03575 0.06964 0.01263
5 4 0.99723 0.03312 0.06537 0.01245
6 5 0.99757 0.03146 0.06115 0.01154
7 6 0.99784 0.03067 0.05716 0.00996
8 7 0.99807 0.03046 0.05351 0.00791
9 8 0.99826 0.03047 0.05026 0.00564
10 9 0.99841 0.03027 0.04742 0.00342
# i 91 more rows
[[16]]
# A tibble: 101 x 5
time w x y z
<int> <dec:.5!> <dec:.5!> <dec:.5!> <dec:.5!>
1 0 0.99508 0.05950 0.07884 0.00834
2 1 0.99543 0.05417 0.07795 0.00998
3 2 0.99583 0.04959 0.07573 0.01138
4 3 0.99625 0.04556 0.07256 0.01228
5 4 0.99665 0.04230 0.06889 0.01263
6 5 0.99701 0.03996 0.06501 0.01235
7 6 0.99731 0.03857 0.06124 0.01144
8 7 0.99757 0.03784 0.05758 0.00995
9 8 0.99781 0.03740 0.05400 0.00803
10 9 0.99803 0.03681 0.05039 0.00590
# i 91 more rows
attr(,"class")
[1] "qts_sample" "list"
$tpca
5 multivariate functional principal components estimated with 3 elements, each.
* * * * * * * * * *
Eigenvalues:
[1] 0.025494786 0.009011399 0.004626775 0.002175458 0.001022167
$var_props
[1] 0.47252278 0.16701812 0.08575308 0.04032015 0.01894495
$total_variance
[1] 0.05395462
$mean_qts
# A tibble: 101 x 5
time w x y z
<int> <dec:.5!> <dec:.5!> <dec:.5!> <dec:.5!>
1 0 0.99484 0.07709 0.06585 0.00272
2 1 0.99525 0.07180 0.06567 0.00335
3 2 0.99570 0.06639 0.06455 0.00409
4 3 0.99616 0.06104 0.06264 0.00461
5 4 0.99659 0.05616 0.06023 0.00482
6 5 0.99698 0.05198 0.05751 0.00464
7 6 0.99731 0.04865 0.05460 0.00406
8 7 0.99760 0.04615 0.05157 0.00310
9 8 0.99784 0.04430 0.04844 0.00181
10 9 0.99806 0.04283 0.04527 0.00027
# i 91 more rows
$principal_qts
$principal_qts[[1]]
# A tibble: 101 x 5
time w x y z
<int> <dec:.5!> <dec:.5!> <dec:.5!> <dec:.5!>
1 0 0.98157 0.03639 0.07900 0.17017
2 1 0.98271 0.03195 0.07968 0.16406
3 2 0.98386 0.02726 0.07949 0.15798
4 3 0.98506 0.02253 0.07856 0.15162
5 4 0.98627 0.01824 0.07710 0.14489
6 5 0.98749 0.01465 0.07529 0.13776
7 6 0.98870 0.01193 0.07322 0.13023
8 7 0.98990 0.01009 0.07098 0.12233
9 8 0.99106 0.00894 0.06860 0.11410
10 9 0.99216 0.00823 0.06619 0.10565
# i 91 more rows
$principal_qts[[2]]
# A tibble: 101 x 5
time w x y z
<int> <dec:.5!> <dec:.5!> <dec:.5!> <dec:.5!>
1 0 0.98215 0.18227 0.03969 0.02418
2 1 0.98344 0.17493 0.04083 0.02421
3 2 0.98473 0.16736 0.04130 0.02424
4 3 0.98601 0.15972 0.04120 0.02393
5 4 0.98720 0.15243 0.04079 0.02314
6 5 0.98826 0.14574 0.04022 0.02178
7 6 0.98919 0.13981 0.03962 0.01984
8 7 0.98997 0.13463 0.03903 0.01734
9 8 0.99066 0.13003 0.03849 0.01434
10 9 0.99127 0.12575 0.03805 0.01093
# i 91 more rows
$principal_qts[[3]]
# A tibble: 101 x 5
time w x y z
<int> <dec:.5!> <dec:.5!> <dec:.5!> <dec:.5!>
1 0 0.99958 0.00594 0.00842 -0.02710
2 1 0.99959 0.00912 0.01582 -0.02186
3 2 0.99955 0.01158 0.02220 -0.01668
4 3 0.99945 0.01348 0.02772 -0.01187
5 4 0.99932 0.01524 0.03266 -0.00752
6 5 0.99915 0.01711 0.03720 -0.00369
7 6 0.99895 0.01927 0.04145 -0.00036
8 7 0.99873 0.02173 0.04543 0.00248
9 8 0.99848 0.02432 0.04917 0.00491
10 9 0.99823 0.02681 0.05271 0.00701
# i 91 more rows
$principal_qts[[4]]
# A tibble: 101 x 5
time w x y z
<int> <dec:.5!> <dec:.5!> <dec:.5!> <dec:.5!>
1 0 0.99862 0.04023 -0.03290 -0.00762
2 1 0.99899 0.03564 -0.02557 -0.00963
3 2 0.99925 0.03140 -0.01945 -0.01141
4 3 0.99943 0.02764 -0.01435 -0.01329
5 4 0.99953 0.02475 -0.00999 -0.01538
6 5 0.99956 0.02293 -0.00615 -0.01776
7 6 0.99954 0.02234 -0.00269 -0.02042
8 7 0.99947 0.02292 0.00044 -0.02332
9 8 0.99935 0.02448 0.00327 -0.02640
10 9 0.99919 0.02675 0.00586 -0.02953
# i 91 more rows
$principal_qts[[5]]
# A tibble: 101 x 5
time w x y z
<int> <dec:.5!> <dec:.5!> <dec:.5!> <dec:.5!>
1 0 0.99416 0.09096 -0.04161 -0.04039
2 1 0.99603 0.07442 -0.02340 -0.04290
3 2 0.99724 0.05847 -0.00731 -0.04514
4 3 0.99791 0.04327 0.00686 -0.04746
5 4 0.99813 0.02922 0.01945 -0.04998
6 5 0.99800 0.01657 0.03071 -0.05276
7 6 0.99759 0.00546 0.04085 -0.05576
8 7 0.99700 -0.00413 0.04995 -0.05894
9 8 0.99629 -0.01238 0.05808 -0.06221
10 9 0.99552 -0.01959 0.06532 -0.06545
# i 91 more rows
attr(,"class")
[1] "prcomp_qts"
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