ordr (version 0.1.1)

methods-lda: 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 lda
as_tbl_ord(x)
# S3 method for lda_ord
as_tbl_ord(x)
# S3 method for lda
recover_rows(x)
# S3 method for lda_ord
recover_rows(x)
# S3 method for lda
recover_cols(x)
# S3 method for lda_ord
recover_cols(x)
# S3 method for lda
recover_inertia(x)
# S3 method for lda_ord
recover_inertia(x)
# S3 method for lda
recover_coord(x)
# S3 method for lda_ord
recover_coord(x)
# S3 method for lda
recover_conference(x)
# S3 method for lda_ord
recover_conference(x)
# S3 method for lda
recover_aug_rows(x)
# S3 method for lda_ord
recover_aug_rows(x)
# S3 method for lda
recover_aug_cols(x)
# S3 method for lda_ord
recover_aug_cols(x)
# S3 method for lda
recover_aug_coord(x)
# S3 method for lda_ord
recover_aug_coord(x)
# S3 method for lda
recover_supp_rows(x)
# S3 method for lda_ord
recover_supp_rows(x)

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.

Arguments

x

An ordination object.

Details

See lda-ord for details.

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)