plot.singleOut function

Plot outliers for single observations

Plot the fitted local regression, confidence intervals and detected outliers for each plotId.

## S3 method for class 'singleOut'
plot(x, ..., plotIds = NULL, outOnly = TRUE, output = TRUE)

Arguments

• x: An object of class singleOut.
• ...: Ignored.
• plotIds: A character vector of plotIds for which the outliers should be detected. If NULL, all plotIds in TP are used.
• outOnly: Should only plots containing outliers be plotted?
• output: Should the plot be output to the current device? If FALSE only a (list of) ggplot object(s) is invisibly returned. Ignored if outFile is specified.

Returns

A list of ggplot objects is invisibly returned.

Examples

## Create a TP object containing the data from the Phenovator.
PhenovatorDat1 <- PhenovatorDat1[!PhenovatorDat1$pos %in%
                                 c("c24r41", "c7r18", "c7r49"), ]
phenoTP <- createTimePoints(dat = PhenovatorDat1,
                            experimentName = "Phenovator",
                            genotype = "Genotype",
                            timePoint = "timepoints",
                            repId = "Replicate",
                            plotId = "pos",
                            rowNum = "y", colNum = "x",
                            addCheck = TRUE,
                            checkGenotypes = c("check1", "check2",
                                               "check3", "check4"))

## Select a subset of plants, for example here 9 plants.
plantSel <- phenoTP[[1]]$plotId[1:9]
# Then run on the subset.
resuVatorHTP <- detectSingleOut(TP = phenoTP,
                               trait = "EffpsII",
                               plotIds = plantSel,
                               confIntSize = 3,
                               nnLocfit = 0.1)

## Visualize the prediction by choosing a single plant...
plot(resuVatorHTP, plotIds = "c21r24", outOnly = FALSE)
## ...or a subset of plants.
plot(resuVatorHTP, plotIds = plantSel, outOnly = FALSE)

See Also

Other functions for detecting outliers for single observations: detectSingleOut(), detectSingleOutMaize(), removeSingleOut()