plotLZM: Plot local z-score mean to assess unbiasedness

In ppernot/ErrViewLib: Library for ErrView

Plot local z-score mean to assess unbiasedness

Description

Plot local z-score mean to assess unbiasedness

Usage

plotLZM(
  X,
  Z,
  aux = NULL,
  logX = FALSE,
  nBin = NULL,
  equiPop = TRUE,
  popMin = 30,
  logBin = TRUE,
  intrv = NULL,
  plot = TRUE,
  slide = FALSE,
  xlab = "Conditioning variable",
  xlim = NULL,
  ylim = NULL,
  title = "",
  add = FALSE,
  col = 5,
  label = 0,
  gPars = ErrViewLib::setgPars()
)

Arguments

X	(vector) abscissae of the Z values
Z	(vector) set of z-score values to be tested
aux	(vector) auxilliary vector to resolve ties in X sorting
logX	(logical) log-transform X
nBin	(integer) number of intervals for local coverage stats
equiPop	(logical) generate intervals with equal bin counts (default: 'equiPop = TRUE')
popMin	(integer) minimal bin count in an interval
logBin	(logical) if 'equiPop = FALSE', one can choose between equal range intervals, or equal log-range intervals (default 'logBin = TRUE')
intrv	(object) intervals generated by 'genIntervals' (default: 'NULL')
plot	(logical) plot the results
slide	(logical) use sliding window for subsetting (X,Z)
xlab	(string) X axis label
xlim	(vector) min and max values of X axis
ylim	(vector) limits of the y axis
title	(string) a title to display above the plot
add	(logical) add to previous graph ?
col	(integer) color index of curve to add
label	(integer) index of letter for subplot tag
gPars	(list) graphical parameters

Value

Invisibly returns a list of LZM results. Mainly used for its plotting side effect.

Examples

  uE  = sqrt(rchisq(1000, df = 4))  # Re-scale uncertainty
  E   = rnorm(uE, mean=0, sd=uE)    # Generate errors
  plotLZM(uE, E/uE, ylim = c(-1,1))

ppernot/ErrViewLib documentation built on June 1, 2024, 4:33 a.m.