This package provides functions for outlier detection in the setting of
replicated data. Assuming we have multiple independent measurements (called
"replicates") for each data point, we can find which sets of measurements are so
different from each other that we can call them outliers. We use the absolute
difference
and coefficient of variation
(Zeta, a kind of relative difference)
for each pair of replicates to make our determinations.
The function outlier_DZ
returns a numeric identifier for the outlier status
(
for non-outlier,
for large
but not
,
and
for
outlier). The other main functions are
q_exp_joint_DZ
, q_exp_marg_DZ
,
q_gg_joint_DZ
, and q_gg_marg_DZ
. Their outputs are probabilities called
-values
that we determine using joint or marginal probability distributions.
Please see {CITE PAPER} for further details and the derivations of these
methods. Also please check the vignette HTML file in the inst/doc
directory.
Currently, outlier_DZ
does not work, because it depends on the extremevalues
package for the getOutliersI
function. This package, in turn, depends on the
tcltk
package, which is now part of base R
. The package extremevalues
should then be able to run without importing tcltk
, but it does not work. If
you are able to get extremevalues
to work locally, the code for outlier_DZ
is in the vignette explaining this method.
To install this package, please install and load the devtools
package and use
the command
install_github("matthew-seth-smith/replicateOutliers")
Travis-CI is throwing errors for this build (as does loading this function on
another computer) because of conflicts between the gompertz
functions used by
the packages VGAM
and flexsurv
. I do not believe this package uses the
Gompertz Distribution, so this should not be a problem.
This project was supported by the Undergraduate Summer Research Fellowship at Fox Chase Cancer Center during the summer of 2018.
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