plot.LPS: Plot method for LPS objects

In LPS: Linear Predictor Score, for Binary Inference from Multiple Continuous Variables

Description

This function plots the distributions of the LPS scores in each group for a fitted LPS object.

Usage

  ## S3 method for class 'LPS'
plot(x, y, method=c("Wright", "Radmacher", "exact"), threshold = 0.9,
    values = FALSE, col.classes = c("#FFCC00", "#1144CC"), xlim, yaxt = "s",
    xlab = "LPS", ylab, las = 0, lwd = 2,...)

Arguments

x	An object of class "LPS", as returned by LPS.
y	Single character value defining y axis : "density" or (bayesian) "probability".
method	Single character value, the method to use for predictions. See predict.LPS.
threshold	Single numeric value, the confidence threshold to use for the "gray zone" (scores for which none of the two groups can be assigned with a probability greater than this threshold). See predict.LPS.
values	Single logical value, whether to plot individual scores from the training series or not.
col.classes	Character vector of two values giving to each class a distinct color.
xlim	To be passed to plot, see plot.default.
yaxt	To be passed to plot, see par.
xlab	To be passed to plot, see plot.default.
ylab	To be passed to plot, see plot.default.
las	To be passed to plot, see par.
lwd	To be passed to plot, see par.
...	Further arguments to be passed to plot or par.

Author(s)

Sylvain Mareschal

See Also

LPS

Examples

  # Data with features in columns
  data(rosenwald)
  group <- rosenwald.cli$group
  expr <- t(rosenwald.expr)
  
  # NA imputation (feature's mean to minimize impact)
  f <- function(x) { x[ is.na(x) ] <- round(mean(x, na.rm=TRUE), 3); x }
  expr <- apply(expr, 2, f)
  
  # Coefficients
  coeff <- LPS.coeff(data=expr, response=group)
  
  # 10 best features model
  m <- LPS(data=expr, coeff=coeff, response=group, k=10)
  
  
  # Distributions of scores in each group
  plot(m, "density")
  
  # Probability for each group along the score axis
  plot(m, "probability", yaxt="s")

Example output

LPS documentation built on May 29, 2021, 5:07 p.m.