nmr_pca_outliers_filter {AlpsNMR} | R Documentation

## Exclude outliers

### Description

Exclude outliers

### Usage

    nmr_pca_outliers_filter(nmr_dataset, pca_outliers)

### Arguments

`nmr_dataset` | An nmr_dataset_1D object
`pca_outliers` | The output from `nmr_pca_outliers()`

### Value

An nmr_dataset_1D without the detected outliers

### See Also

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

Other outlier detection functions: `Pipelines`, `nmr_pca_outliers_plot()`, `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_plot()`, `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()`

Other subsetting functions: `[.nmr_dataset_1D()`, `[.nmr_dataset_peak_table()`, `[.nmr_dataset()`, `filter.nmr_dataset_family()`

### 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)
    dataset_whitout_outliers <- nmr_pca_outliers_filter(dataset_1D, outliers_info)

[Package AlpsNMR version 3.0.6 Index]