WVPlots (version 1.3.0)

GainCurvePlotC: Plot the cumulative gain curve of a sort-order with costs.

Description

Plot the cumulative gain curve of a sort-order with costs.

Usage

GainCurvePlotC(
  frame,
  xvar,
  costVar,
  truthVar,
  title,
  ...,
  estimate_sig = FALSE,
  large_count = 1000,
  model_color = "darkblue",
  wizard_color = "darkgreen",
  shadow_color = "darkgray"
)

Arguments

frame

data frame to get values from

xvar

name of the independent (input or model score) column in frame

costVar

cost of each item (drives x-axis sum)

truthVar

name of the dependent (output or result to be modeled) column in frame

title

title to place on plot

...

no unnamed argument, added to force named binding of later arguments.

estimate_sig

logical, if TRUE compute significance

large_count

numeric, upper bound target for number of plotting points

model_color

color for the model curve

wizard_color

color for the "wizard" (best possible) curve

shadow_color

color for the shaded area under the curve

Details

GainCurvePlotC plots a cumulative gain curve for the case where items have an additional cost, in addition to an outcome value.

The x-axis represents the fraction of total cost experienced when items are sorted by score, and the y-axis represents the cumulative summed true outcome represented by the items seen so far.

For comparison, GainCurvePlotC also plots the "wizard curve": the gain curve when the data is sorted according to its true outcome/cost (the optimal sort order).

To improve presentation quality, the plot is limited to approximately large_count points (default: 1000). For larger data sets, the data is appropriately randomly sampled down before plotting.

See Also

GainCurvePlot

Examples

# NOT RUN {
set.seed(34903490)
y = abs(rnorm(20)) + 0.1
x = abs(y + 0.5*rnorm(20))
frm = data.frame(model=x, value=y)
frm$costs=1
frm$costs[1]=5
WVPlots::GainCurvePlotC(frm, "model", "costs", "value",
   title="Example Continuous Gain CurveC")

# }