residualPlot: generates a ggplot object of the residual plot of a...
In BenBruyneel/BBPersonalR: BBPersonalR

residualPlot

R Documentation

generates a ggplot object of the residual plot of a calibration table

Description

generates a ggplot object of the residual plot of a calibration table

Usage

residualPlot(
  fitTable,
  predictorColumn = 1,
  responseColumn = 2,
  weights = NULL,
  fit = fitLM(fitTable, predictorColumn = predictorColumn, responseColumn =
    responseColumn, weights = weights),
  title = "",
  figureNo = 2,
  caption = paste(c("Figure ", figureNo, ": Residual Plot"), collapse = ""),
  standardized = TRUE,
  showLimits = TRUE,
  limits = stdResidualLimits(),
  fitColor = "red",
  fitLineType = 1,
  fitWidth = 1,
  fitAlpha = 1,
  pointsColor = "Black",
  pointsFill = "black",
  pointsShape = 21,
  pointsSize = 2,
  pointsAlpha = 1,
  autoScaleX = TRUE,
  xLimits = c(0, "N/A"),
  xLabel = NULL,
  xOob = 2,
  autoScaleY = TRUE,
  yLimits = c(0, "N/A"),
  yLabel = NULL,
  yOob = 2,
  usePredictor = TRUE,
  useYLabel = TRUE,
  rotateGraph = FALSE,
  xOptions = "1",
  yOptions = "1"
)

Arguments

`fitTable`	data.frame containing the data to be fitted
`predictorColumn`	can be integer (column number) or character (column name)
`responseColumn`	can be integer (column number) or character (column name)
`weights`	default = NULL, otherwise must be integer to give weights to the predictor values (see also function weightsVector) or a numeric vector with length = number of rows in calibrationTable. Note: if a vector of weights if provided, the prediction to the minimal/maximal values on the x- & y-axis is not possible
`fit`	model object (eg coming from lm() or fitLM())
`title`	title for the graph, character vector
`figureNo`	number of the figure, used for the caption ("Figure ..." )
`caption`	caption for the graph, character vector
`standardized`	if TRUE: use standardized residuals
`showLimits`	if TRUE, draw the lines for the limits defined in limits
`limits`	definition of the limits to draw, see stdLiits, zeroLimits for examples
`fitColor`	defines color of loess-type 'fit' to the residual coordinates
`fitLineType`	defines line type of the 'fit' to the residual coordinates
`fitWidth`	defines line width of the 'fit' to the residual coordinates
`fitAlpha`	defines alpha of the 'fit' to the residual coordinates
`pointsColor`	(border) color of the datapoints
`pointsFill`	fill color, note: only some shapes have a fill color
`pointsShape`	shape of the datapoints (default = 21), see vignette ggplot2::ggplot2-specs
`pointsSize`	size of the datapoints
`pointsAlpha`	alpha ('seethrough' value) of the datapoints
`autoScaleX`	if TRUE then default autoscaling of the x-axis takes place, most other settings delaing with scaling of the x-axis the are then ignored
`xLimits`	2 element numeric vector with the minimum and maximum value for the x-axis. If an element is a character vector or something that cannot be converted to a numeric value, then NA is used which leads to minimum/maximum value
`xLabel`	name of the x-axis, character vector
`xOob`	integer vector, indicating how to deal with out of bounds datapoints. 1 = censor scales::oob_censor is used, 2 = infinite, scales::oob_squish_infinite is used. Note: x-axis only
`autoScaleY`	if TRUE then default autoscaling of the y-axis takes place, most other settings delaing with scaling of the y-axis the are then ignored
`yLimits`	2 element numeric vector with the minimum and maximum value for the y-axis. If an element is a character vector or something that cannot be converted to a numeric value, then NA is used which leads to minimum/maximum value
`yLabel`	name of the y-axis, character vector
`yOob`	integer vector, indicating how to deal with out of bounds datapoints. 1 = censor scales::oob_censor is used, 2 = infinite, scales::oob_squish_infinite is used. Note: y-axis only
`usePredictor`	if TRUE then the predictor is used as x-axis
`useYLabel`	if TRUE then the y-label is used
`rotateGraph`	if TRUE, then x-axis and y-axis are swapped, essentially resulting in a graph rotated 90 degrees
`xOptions`	x-axis options character vector, "1" normal scale, "2" reversed scale, "3" logarithmic scale (log10)
`yOptions`	y-axis options character vector, "1" normal scale, "2" reversed scale,"3" logarithmic scale (log10)