methods-lda | R Documentation |
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()
.
## 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)
x |
An ordination object. |
See lda-ord for details.
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 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
# 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)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.