plotOutliers {geomorph} | R Documentation |
Find potential outliers
Description
Function plots all specimens ordered by distance from the mean.
Usage
plotOutliers(A, groups = NULL, inspect.outliers = FALSE)
Arguments
A |
A 3D array (p x k x n) containing Procrustes shape variables for a set of specimens |
groups |
An optional factor defining groups |
inspect.outliers |
A logical value indicating whether to plot outlier shape configurations as compared to the consensus |
Details
The function creates a plot of all specimens ordered by their Procrustes distance from the mean shape.
The median distance (unbroken line) and upper and lower quartiles (dashed lines) summarize the distances
from the mean shape. Specimens falling above the upper quartile are plotted in red. The user may optionally
also inspect the shapes of identified outlier configurations as compared to the consensus, in order
to identify digitization errors or other data issues. The addresses of all specimens are
returned in the order displayed in the plot for further inspection by plotRefToTarget
.
If the data have strong group structure and there is reasonable belief that the whole sample mean should not be used, then a factor defining the groups can be used.
Value
Function returns the landmark addresses of all specimens ordered as in the plot. If groups are used, function returns a list structure and a plot for each level in groups.
Author(s)
Emma Sherratt & Antigoni Kaliontzopoulou
See Also
Examples
## Not run:
data(plethodon)
# let's make some outliers
newland <- plethodon$land
newland[c(1,8),,2] <- newland[c(8,1),,2]
newland[c(3,11),,26] <- newland[c(11,3),,2]
Y<- gpagen(newland) # GPA
out <- plotOutliers(Y$coords) # function returns dimnames and address
# of all specimens ordered
plotOutliers(Y$coords, inspect.outliers = TRUE) # function also produces
# plots of identified outlier specimens compared to the mean shape
# example with groups
plotOutliers(Y$coords, groups = plethodon$species,
inspect.outliers = TRUE)
## End(Not run)