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Evaluate outliers in Data

Source: R/outlier_check.R
outlier_table.Rd

outlier_table() returns a summary table which shows summary statistics of a variable after applying several outlier filters.

Usage

outlier_table(dat, project, x, sd_val = NULL, log_fun = TRUE)

Arguments

dat

Primary data containing information on hauls or trips. Table in the FishSET database contains the string 'MainDataTable'.

project

String, name of project.

x

Variable or column number in dat to check for outliers.

sd_val

Optional. Number of standard deviations from mean defining outliers. For example, sd_val = 4 would mean values outside +/- 4 SD from the mean would be outliers.

log_fun

Logical, whether to log function call (for internal use).

Value

Table for evaluating whether outliers may exist in the selected data column.

Details

Returns a table of summary statistics (mean, median, standard deviation, minimum, maximum, number of NAs, and skew of the data) for x after values outside the outlier measure have been removed. Outlier measures include 5-95% quantiles, 25-75% quantiles, mean +/-2SD, mean +/-3SD, median +/-2SD, and median +/-3SD. Only one variable can be checked at a time. Table is saved to the Output folder.

Examples

if (FALSE) {
outlier_table(pollockMainDataTable, 'pollock', x = 'HAUL')
}