methods-lda {ordr} | R Documentation |
Functionality for linear discriminant analysis ('lda') objects
Description
These methods extract data from, and attribute new data to,
objects of class "lda"
and "lda_ord"
as returned by MASS::lda()
and
lda_ord()
.
Usage
## S3 method for class 'lda'
as_tbl_ord(x)
## S3 method for class 'lda_ord'
as_tbl_ord(x)
## S3 method for class 'lda'
recover_rows(x)
## S3 method for class 'lda_ord'
recover_rows(x)
## S3 method for class 'lda'
recover_cols(x)
## S3 method for class 'lda_ord'
recover_cols(x)
## S3 method for class 'lda'
recover_inertia(x)
## S3 method for class 'lda_ord'
recover_inertia(x)
## S3 method for class 'lda'
recover_coord(x)
## S3 method for class 'lda_ord'
recover_coord(x)
## S3 method for class 'lda'
recover_conference(x)
## S3 method for class 'lda_ord'
recover_conference(x)
## S3 method for class 'lda'
recover_aug_rows(x)
## S3 method for class 'lda_ord'
recover_aug_rows(x)
## S3 method for class 'lda'
recover_aug_cols(x)
## S3 method for class 'lda_ord'
recover_aug_cols(x)
## S3 method for class 'lda'
recover_aug_coord(x)
## S3 method for class 'lda_ord'
recover_aug_coord(x)
## S3 method for class 'lda'
recover_supp_rows(x)
## S3 method for class 'lda_ord'
recover_supp_rows(x)
Arguments
x |
An ordination object. |
Details
See lda-ord for details.
Value
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.
See Also
Other methods for singular value decomposition-based techniques:
methods-cancor
,
methods-correspondence
,
methods-lra
,
methods-mca
,
methods-prcomp
,
methods-princomp
,
methods-svd
Other models from the MASS package:
methods-correspondence
,
methods-mca
Examples
# data frame of Anderson iris species measurements
class(iris)
head(iris)
# default (unstandardized discriminant) coefficients
lda_ord(iris[, 1:4], iris[, 5]) %>%
as_tbl_ord() %>%
print() -> iris_lda
# recover centroid coordinates and measurement discriminant coefficients
get_rows(iris_lda, elements = "active")
head(get_rows(iris_lda, elements = "score"))
get_cols(iris_lda)
# augment ordination with centroid and measurement names
augment_ord(iris_lda)