visualFields (version 0.6.2)

tdrankadjperc: percentiles for adjusted TD rank curve

Description

gets percentiles for adjusted TD rank curve

Usage

tdrankadjperc( td, percentiles = c( 0.5, 1, 2, 5, 95 ), type = "conventional",
               typequantiles = c( "quantile", "(i-1)/(n-1)", "i/(n+1)", "i/n" ),
               smooth = TRUE, smoothFunction = tdrankglm )

Arguments

td

vf-object with total-deviation values

type

whether to use a conventional way to plot the rank TD curve or ghrank type where the vf object passed is the reconstructed within-normal TD rank curve. Default is conventional

percentiles

percentiles at which to calculate cutoff values

typequantiles

see wtd.quantile for a list of different options

smooth

whether to use a function to smooth the results or not. Default is TRUE

smoothFunction

if smooth is TRUE is true, the function to use for smoothing. Default is tdrankglm, a GLM fit which was proven to do a good fit for average over subject of TD rank curves. This function is not really a smoothing procedure, but a parametric fit

Value

percentiles for adjusted TD rank curves

See Also

tdrank, tdrankperc

Examples

# NOT RUN {
  td <- tdval( vf91016right )
  tdr <- tdrankadjperc( td )
# }