nested_prcomp {tidypaleo} | R Documentation |
Nested Principal Components Analysis (PCA)
Description
Powered by prcomp. When creating the nested_data,
the data should be scaled (i.e, trans = scale
) if all variables are not
in the same unit.
Usage
nested_prcomp(.data, data_column = .data$data, ...)
Arguments
.data |
A data frame with a list column of data frames, possibly created using nested_data. |
data_column |
An expression that evalulates to the data object within each row of .data |
... |
Passed to prcomp. |
Value
.data with additional columns 'model', 'loadings', 'variance' and 'scores'
Examples
library(dplyr, warn.conflicts = FALSE)
nested_pca <- alta_lake_geochem %>%
nested_data(
qualifiers = c(depth, zone),
key = param,
value = value,
trans = scale
) %>%
nested_prcomp()
# get variance info
nested_pca %>% unnested_data(variance)
# get loadings info
nested_pca %>% unnested_data(loadings)
# scores, requalified
nested_pca %>% unnested_data(c(qualifiers, scores))
[Package tidypaleo version 0.1.3 Index]