# subset QS data to rank variables
qs_ranks <- subset(
qswur_usa,
complete.cases(qswur_usa),
select = 8:13
)
head(qs_ranks)
# eigendecomposition of Kendall correlation matrix
qs_ranks %>%
cor(method = "kendall") %>%
eigen() %>%
print() -> qs_eigen
# recover eigenvectors
get_rows(qs_eigen)
identical(get_cols(qs_eigen), get_rows(qs_eigen))
# wrap as a 'tbl_ord'
as_tbl_ord(qs_eigen)
# same eigendecomposition, preserving row names and adding column names
qs_ranks %>%
cor(method = "kendall") %>%
eigen_ord() %>%
print() -> qs_eigen
# wrap as a 'tbl_ord' and augment with dimension names
augment_ord(as_tbl_ord(qs_eigen))
# decomposition returns pure eigenvectors
get_conference(qs_eigen)
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