methods-eigen | R Documentation |
These methods extract data from, and attribute new data to,
objects of class "eigen"
returned by base::eigen()
when the parameter
only.values
is set to FALSE
or of class "eigen_ord"
returned by
eigen_ord()
.
## S3 method for class 'eigen'
as_tbl_ord(x)
## S3 method for class 'eigen'
recover_rows(x)
## S3 method for class 'eigen'
recover_cols(x)
## S3 method for class 'eigen'
recover_inertia(x)
## S3 method for class 'eigen'
recover_coord(x)
## S3 method for class 'eigen'
recover_conference(x)
## S3 method for class 'eigen_ord'
recover_aug_rows(x)
## S3 method for class 'eigen_ord'
recover_aug_cols(x)
## S3 method for class 'eigen'
recover_aug_coord(x)
## S3 method for class 'eigen_ord'
as_tbl_ord(x)
## S3 method for class 'eigen_ord'
recover_rows(x)
## S3 method for class 'eigen_ord'
recover_cols(x)
## S3 method for class 'eigen_ord'
recover_inertia(x)
## S3 method for class 'eigen_ord'
recover_coord(x)
## S3 method for class 'eigen_ord'
recover_conference(x)
## S3 method for class 'eigen_ord'
recover_aug_rows(x)
## S3 method for class 'eigen_ord'
recover_aug_cols(x)
## S3 method for class 'eigen_ord'
recover_aug_coord(x)
x |
An ordination object. |
base::eigen()
usually returns an object of class "eigen"
, which contains
the numerical eigendecomposition without annotations such as row and column
names. To facilitate downstream analysis, eigen_ord()
returns a modified
'eigen' object with row names taken (if available) from the original data and
column names indicating the integer index of each eigenvector.
The recovery generics recover_*()
return core model components, distribution of inertia,
supplementary elements, and intrinsic metadata; but they require methods for each model class to
tell them what these components are.
The generic as_tbl_ord()
returns its input wrapped in the 'tbl_ord'
class. Its methods determine what model classes it is allowed to wrap. It
then provides 'tbl_ord' methods with access to the recoverers and hence to
the model components.
Other methods for eigen-decomposition-based techniques:
methods-cmds
,
methods-factanal
,
methods-princomp
Other models from the base package:
methods-svd
# eigendecompose covariance matrix of ability tests
gi_eigen <- eigen(ability.cov$cov)
# recover eigenvectors
get_rows(gi_eigen)
identical(get_cols(gi_eigen), get_rows(gi_eigen))
# wrap as a 'tbl_ord'
as_tbl_ord(gi_eigen)
# same eigendecomposition, preserving names
gi_eigen <- eigen_ord(ability.cov$cov)
# wrap as a 'tbl_ord' and augment with dimension names
augment_ord(as_tbl_ord(gi_eigen))
# decomposition returns pure eigenvectors
get_conference(gi_eigen)
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