plot.nplr: Plotting 'nplr' Objects

In fredcommo/nplr: N-Parameter Logistic Regression

Description

This function allows visualizing logistic models fitted using nplr.

Usage

  ## S3 method for class 'nplr'
plot(x, pcol = "aquamarine1", lcol = "red3",
  showEstim = FALSE, showCI = TRUE, showGOF = TRUE, showInfl = FALSE,
  showPoints = TRUE, showSDerr = FALSE, B = 1e4, conf.level = .95, unit = "", ...)

Arguments

x	: an object of class nplr
pcol	: the points color.
lcol	: the line color.
showEstim	: logical/numeric. If a numerical value is passed (a y value to reach), the estimated x value , and interval, is displayed on the plot. Default is FALSE
showCI	: logical. show the estimated confidence interval
showGOF	: logical. show the estimated goodness-of-fit.
showInfl	: logical. add the inflexion point on the plot.
showPoints	: logical. add the points on the plot.
showSDerr	: logical. add the standard errors on the plot (maybe useful in case of experiment with replicates).
B	: the length of simulated y values. Used to estimate the confidence interval
conf.level	: the confidence level. See getEstimates
unit	: the unit to specify when showEstim is TRUE. Default is an empty string.
...	: other graphical parameters. See par.

Details

None

Note

The data used in the examples are samples from the NCI-60 Growth Inhibition Data:
https://wiki.nci.nih.gov/display/NCIDTPdata/NCI-60+Growth+Inhibition+Data, except for multicell.tsv which are simulated data.

Source

None

References

None

See Also

overlay

Examples

# Using the PC-3 data
  require(nplr)
  path <- system.file("extdata", "pc3.txt", package = "nplr")
  pc3 <- read.delim(path)
  model <- nplr(x = pc3$CONC, y = pc3$GIPROP)
  plot(model, showEstim = 0.5, unit = "nM")

fredcommo/nplr documentation built on May 16, 2019, 2:41 p.m.