Code
vespa64$igp[1]
Output
[[1]]
# A tibble: 101 x 5
time w x y z
<int> <dec:.5!> <dec:.5!> <dec:.5!> <dec:.5!>
1 0 0.99427 0.07973 0.06988 0.01334
2 1 0.99483 0.07457 0.06763 0.01313
3 2 0.99542 0.06931 0.06457 0.01269
4 3 0.99602 0.06398 0.06091 0.01184
5 4 0.99652 0.05949 0.05742 0.01070
6 5 0.99694 0.05572 0.05403 0.00932
7 6 0.99729 0.05275 0.05079 0.00772
8 7 0.99757 0.05056 0.04761 0.00583
9 8 0.99782 0.04883 0.04430 0.00366
10 9 0.99805 0.04730 0.04071 0.00125
# i 91 more rows
attr(,"class")
[1] "qts_sample" "list"
Code
rnorm_qts(1, vespa64$igp[[1]])
Output
[[1]]
# A tibble: 101 x 5
time w x y z
<int> <dec:.5!> <dec:.5!> <dec:.5!> <dec:.5!>
1 0 0.99840 -0.04080 0.02253 0.03190
2 1 0.99819 -0.04462 0.02061 0.03480
3 2 0.99823 -0.04494 0.01533 0.03572
4 3 0.99740 -0.06064 0.00801 0.03824
5 4 0.99697 -0.06308 0.00531 0.04529
6 5 0.99672 -0.06448 -0.00204 0.04884
7 6 0.99642 -0.06989 -0.00447 0.04733
8 7 0.99639 -0.07440 -0.00602 0.04043
9 8 0.99606 -0.07852 -0.00951 0.04009
10 9 0.99573 -0.08389 -0.01392 0.03586
# i 91 more rows
attr(,"class")
[1] "qts_sample" "list"
Code
qts_list[[1]]
Output
# A tibble: 101 x 5
time w x y z
<dbl> <dec:.5!> <dec:.5!> <dec:.5!> <dec:.5!>
1 0 0.99956 -0.01849 0.02258 -0.00497
2 1 0.99960 -0.01996 0.01945 -0.00491
3 2 0.99962 -0.02170 0.01592 -0.00514
4 3 0.99962 -0.02412 0.01211 -0.00573
5 4 0.99960 -0.02614 0.00892 -0.00643
6 5 0.99956 -0.02801 0.00619 -0.00707
7 6 0.99953 -0.02946 0.00407 -0.00758
8 7 0.99951 -0.03028 0.00242 -0.00807
9 8 0.99949 -0.03072 0.00100 -0.00865
10 9 0.99948 -0.03085 -0.00056 -0.00936
# i 91 more rows
Code
qts_list[[1]]
Output
# A tibble: 101 x 5
time w x y z
<int> <dec:.5!> <dec:.5!> <dec:.5!> <dec:.5!>
1 0 0.99719 0.06241 0.04023 0.00987
2 1 0.99746 0.05897 0.03873 0.00967
3 2 0.99774 0.05548 0.03669 0.00932
4 3 0.99802 0.05194 0.03426 0.00869
5 4 0.99826 0.04896 0.03195 0.00787
6 5 0.99845 0.04646 0.02970 0.00689
7 6 0.99861 0.04450 0.02756 0.00578
8 7 0.99874 0.04306 0.02546 0.00448
9 8 0.99885 0.04192 0.02328 0.00300
10 9 0.99894 0.04091 0.02091 0.00135
# i 91 more rows
Code
mean(vespa64$igp)
Output
# A tibble: 101 x 5
time w x y z
<int> <dec:.5!> <dec:.5!> <dec:.5!> <dec:.5!>
1 0 0.99406 0.09402 0.05288 0.01472
2 1 0.99445 0.08937 0.05352 0.01464
3 2 0.99487 0.08469 0.05348 0.01450
4 3 0.99527 0.08033 0.05280 0.01415
5 4 0.99564 0.07651 0.05164 0.01351
6 5 0.99597 0.07328 0.05011 0.01254
7 6 0.99627 0.07059 0.04825 0.01122
8 7 0.99655 0.06832 0.04607 0.00960
9 8 0.99682 0.06631 0.04356 0.00773
10 9 0.99707 0.06439 0.04079 0.00570
# i 91 more rows
Code
median(vespa64$igp)
Output
# A tibble: 101 x 5
time w x y z
<int> <dec:.5!> <dec:.5!> <dec:.5!> <dec:.5!>
1 0 0.99394 0.09157 0.05888 0.01513
2 1 0.99439 0.08642 0.05913 0.01490
3 2 0.99482 0.08181 0.05855 0.01465
4 3 0.99525 0.07752 0.05723 0.01414
5 4 0.99565 0.07364 0.05544 0.01338
6 5 0.99603 0.07017 0.05331 0.01236
7 6 0.99638 0.06712 0.05089 0.01105
8 7 0.99671 0.06452 0.04823 0.00938
9 8 0.99701 0.06221 0.04533 0.00742
10 9 0.99729 0.05996 0.04228 0.00530
# i 91 more rows
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