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Identify Fossils with Outlier Age

Source: R/cf_age.R
cf_age.Rd

Removes or flags records that are temporal outliers based on interquantile ranges.

Usage

cf_age(
  x,
  lon = "decimalLongitude",
  lat = "decimalLatitude",
  min_age = "min_ma",
  max_age = "max_ma",
  taxon = "accepted_name",
  method = "quantile",
  size_thresh = 7,
  mltpl = 5,
  replicates = 5,
  flag_thresh = 0.5,
  uniq_loc = FALSE,
  value = "clean",
  verbose = TRUE
)

Arguments

x

data.frame. Containing fossil records with taxon names, ages, and geographic coordinates.

lon

character string. The column with the longitude coordinates. To identify unique records if uniq_loc = TRUE. Default = “decimalLongitude”.

lat

character string. The column with the longitude coordinates. Default = “decimalLatitude”. To identify unique records if uniq_loc = T.

min_age

character string. The column with the minimum age. Default = “min_ma”.

max_age

character string. The column with the maximum age. Default = “max_ma”.

taxon

character string. The column with the taxon name. If “”, searches for outliers over the entire dataset, otherwise per specified taxon. Default = “accepted_name”.

method

character string. Defining the method for outlier selection. See details. Either “quantile” or “mad”. Default = “quantile”.

size_thresh

numeric. The minimum number of records needed for a dataset to be tested. Default = 10.

mltpl

numeric. The multiplier of the interquartile range (method == 'quantile') or median absolute deviation (method == 'mad') to identify outliers. See details. Default = 5.

replicates

numeric. The number of replications for the distance matrix calculation. See details. Default = 5.

flag_thresh

numeric. The fraction of passed replicates necessary to pass the test. See details. Default = 0.5.

uniq_loc

logical. If TRUE only single records per location and time point (and taxon if taxon != "") are used for the outlier testing. Default = T.

value

character string. Defining the output value. See value.

verbose

logical. If TRUE reports the name of the test and the number of records flagged.

Value

Depending on the ‘value’ argument, either a data.frame containing the records considered correct by the test (“clean”) or a logical vector (“flagged”), with TRUE = test passed and FALSE = test failed/potentially problematic . Default = “clean”.

Details

The outlier detection is based on an interquantile range test. A temporal distance matrix among all records is calculated based on a single point selected by random between the minimum and maximum age for each record. The mean distance for each point to all neighbours is calculated and the sum of these distances is then tested against the interquantile range and flagged as an outlier if \(x > IQR(x) + q_75 * mltpl\). The test is replicated ‘replicates’ times, to account for dating uncertainty. Records are flagged as outliers if they are flagged by a fraction of more than ‘flag.thresh’ replicates. Only datasets/taxa comprising more than ‘size_thresh’ records are tested. Distance are calculated as Euclidean distance.

Note

See https://ropensci.github.io/CoordinateCleaner/ for more details and tutorials.

See also

Other fossils: cf_equal(), cf_outl(), cf_range(), write_pyrate()

Examples


minages <- c(runif(n = 11, min = 10, max = 25), 62.5)
x <- data.frame(species = c(letters[1:10], rep("z", 2)),
                min_ma = minages,
                max_ma = c(minages[1:11] + runif(n = 11, min = 0, max = 5), 65))

cf_age(x, value = "flagged", taxon = "")
#> Testing temporal outliers on dataset level
#> Flagged 1 records.
#>     1     2     3     4     5     6     7     8     9    10    11    12 
#>  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE FALSE 

# unique locations only
x <- data.frame(species = c(letters[1:10], rep("z", 2)),
                decimalLongitude = c(runif(n = 10, min = 4, max = 16), 75, 7),
                decimalLatitude = c(runif(n = 12, min = -5, max = 5)),
                min_ma = minages, 
                max_ma = c(minages[1:11] + runif(n = 11, min = 0, max = 5), 65))

cf_age(x, value = "flagged", taxon = "", uniq_loc = TRUE)
#> Testing temporal outliers on dataset level
#> Flagged 1 records.
#>     1     2     3     4     5     6     7     8     9    10    11    12 
#>  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE FALSE