nmr_pca_outliers_plot: Plot for outlier detection diagnostic

In AlpsNMR: Automated spectraL Processing System for NMR

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_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()

Other nmr_dataset_1D functions: [.nmr_dataset_1D(), computes_peak_width_ppm(), file_lister(), files_to_rDolphin(), format.nmr_dataset_1D(), is.nmr_dataset_1D(), load_and_save_functions, new_nmr_dataset_1D(), nmr_align_find_ref(), nmr_baseline_removal(), nmr_baseline_threshold(), nmr_exclude_region(), nmr_integrate_regions(), nmr_interpolate_1D(), nmr_meta_add(), nmr_meta_export(), nmr_meta_get_column(), nmr_meta_get(), nmr_normalize(), nmr_pca_build_model(), nmr_pca_outliers_filter(), nmr_pca_outliers_robust(), nmr_pca_outliers(), nmr_ppm_resolution(), plot.nmr_dataset_1D(), plot_webgl(), print.nmr_dataset_1D(), rdCV_PLS_RF_ML(), rdCV_PLS_RF(), save_files_to_rDolphin(), to_ChemoSpec(), validate_nmr_dataset_peak_table(), validate_nmr_dataset()

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)

AlpsNMR documentation built on April 1, 2021, 6:02 p.m.