dilp (version 1.1.0)

dilp_outliers: Identify outlier specimens

Description

dilp_outliers() will typically only be called internally by dilp(). However, it can be used on its own to locate specimens that may have been misreported or measured incorrectly. dilp_outliers() returns a data frame listing specimens that have unusually high or low values for the four key parameters used in DiLP analyses. If flagged, it may be worth taking a look at the raw measurements and evaluating if the specimen should be used.

Usage

dilp_outliers(specimen_data)

Value

A 4 by X data frame. Each row represents one of the DiLP parameters, and the specimens that are outliers for that parameter.

Arguments

specimen_data

Processed specimen level leaf physiognomic data. The structure should match the structure of the output from dilp_processing()

Examples

# Check for outliers in the provided McAbeeExample dataset. Each
# of these outliers has been manually re-examined and was found acceptable.
dilp_dataset <- dilp_processing(McAbeeExample)
dilp_outliers <- dilp_outliers(dilp_dataset)
dilp_outliers