nmr_pca_outliers_plot: Plot for outlier detection diagnostic

In sipss/AlpsNMR: Automated spectraL Processing System for NMR

Plot for outlier detection diagnostic

Description

Plot for outlier detection diagnostic

Usage

nmr_pca_outliers_plot(nmr_dataset, pca_outliers, ...)

Arguments

nmr_dataset	An nmr_dataset_1D object
pca_outliers	The output from nmr_pca_outliers()
...	Additional parameters passed on to ggplot2::aes() (or now deprecated to ggplot2::aes_string())

Value

A plot for the outlier detection

See Also

Other PCA related functions: nmr_pca_build_model(), nmr_pca_outliers_filter(), nmr_pca_outliers_robust(), nmr_pca_outliers(), nmr_pca_plots

Other outlier detection functions: Pipelines, nmr_pca_outliers_filter(), nmr_pca_outliers_robust(), nmr_pca_outliers()

Examples

# dir_to_demo_dataset <- system.file("dataset-demo", package = "AlpsNMR")
# dataset <- nmr_read_samples_dir(dir_to_demo_dataset)
# dataset_1D <- nmr_interpolate_1D(dataset, axis = c(min = -0.5, max = 10, by = 2.3E-4))
# model <- nmr_pca_build_model(dataset_1D)
# outliers_info <- nmr_pca_outliers(dataset_1D, model)
# nmr_pca_outliers_plot(dataset_1D, outliers_info)

sipss/AlpsNMR documentation built on June 29, 2023, 6:51 a.m.