Code
centring(x = vespa64$igp[[1]], standardize = FALSE, keep_summary_stats = FALSE)
Output
# A tibble: 101 x 5
time w x y z
<int> <dec:.5!> <dec:.5!> <dec:.5!> <dec:.5!>
1 0 0.99364 0.09383 0.06049 0.01484
2 1 0.99425 0.08868 0.05824 0.01455
3 2 0.99489 0.08343 0.05518 0.01401
4 3 0.99553 0.07811 0.05153 0.01307
5 4 0.99606 0.07365 0.04805 0.01184
6 5 0.99650 0.06989 0.04468 0.01037
7 6 0.99686 0.06694 0.04146 0.00869
8 7 0.99714 0.06478 0.03830 0.00674
9 8 0.99738 0.06307 0.03503 0.00451
10 9 0.99761 0.06156 0.03147 0.00204
# i 91 more rows
Code
centring(x = vespa64$igp[[1]], standardize = TRUE, keep_summary_stats = FALSE)
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
centring(x = vespa64$igp[[1]], standardize = FALSE, keep_summary_stats = TRUE)
Output
$qts
# A tibble: 101 x 5
time w x y z
<int> <dec:.5!> <dec:.5!> <dec:.5!> <dec:.5!>
1 0 0.99364 0.09383 0.06049 0.01484
2 1 0.99425 0.08868 0.05824 0.01455
3 2 0.99489 0.08343 0.05518 0.01401
4 3 0.99553 0.07811 0.05153 0.01307
5 4 0.99606 0.07365 0.04805 0.01184
6 5 0.99650 0.06989 0.04468 0.01037
7 6 0.99686 0.06694 0.04146 0.00869
8 7 0.99714 0.06478 0.03830 0.00674
9 8 0.99738 0.06307 0.03503 0.00451
10 9 0.99761 0.06156 0.03147 0.00204
# i 91 more rows
$mean
[1] 0.9998551535 -0.0143000963 0.0092262363 0.0002360886
$sd
[1] 0
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