outlierSTA | R Documentation |
Function to identify observations with standardized residuals exceeding
rLimit
. If not provided rLimit
is computed as
qnorm(1 - 0.5 / rDf)
where rDf
is the residual degrees
of freedom for the model. This value is then restricted to the interval
2..4. Alternatively a custom limit may be provided.
If verbose = TRUE
a summary is printed of outliers and observations
that have the same value for commonFactors
. The column outlier in the
output can be used to distinguish real outliers from observations included
because of their commonFactors.
outlierSTA(
STA,
trials = NULL,
traits = NULL,
what = NULL,
rLimit = NULL,
commonFactors = NULL,
verbose = TRUE
)
STA |
An object of class |
trials |
A character vector specifying the trials for which outliers
should be identified. If |
traits |
A character vector specifying the traits for which outliers should be identified. |
what |
A character string indicating whether the outliers should be
identified for the fitted model with genotype as fixed
( |
rLimit |
A numerical value used for determining when a value is
considered an outlier. All observations with standardized residuals
exceeding |
commonFactors |
A character vector specifying the names of columns
in |
verbose |
Should the outliers be printed to the console? |
A list with two components:
indicator - a list of numeric vectors indicating the location of the outliers in the data
outliers - a data.frame containing the outliers and observations
similar to the outliers as defined by commonFactors
## Fit a model using lme4.
modLme <- fitTD(TD = TDHeat05,
traits = "yield",
design = "res.rowcol",
engine = "lme4")
## Detect outliers in the standardized residuals of the fitted model.
outliers <- outlierSTA(STA = modLme,
traits = "yield")
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