valorate.plot.empirical: PLOT THE SAMPLED (EMPIRICAL) LOG-RANK DISTRIBUTION
In valorate: Velocity and Accuracy of the LOg-RAnk TEst

Description Usage Arguments Details Value Author(s) References See Also Examples

Plots the estimated density of the log-rank distribution.

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valorate.plot.empirical(vro, n1, vstat, type, log, add, include, xlab, ylab, 
	main, samp, smooth, legends, shades, transparency, lwd, xlim, 
	minL=NA, minR=NA, ...)

`vro`	the valorate object.
`n1`	the size of the 'mutated' or interested survival group. It can be also the numerical/logical 'x' vector as in valorate.survdiff in which case n1 and vstat are estimated.
`vstat`	log-rank statistic. If provided, a vertical mark on this value is shown and both sides of the density are filled to highlight areas.
`type`	typical plot parameter: "p"=points, "l"=lines (default), "o"=overlap.
`log`	typical plot parameter : specify which axis are shown in logarithm base 10.
`add`	typical plot parameter : specify whether the plot is new or added to an existing one.
`include`	specify which other estimations are included. This is experimental. Default "none", possibles: "none","gaussian","beta","weibull","all".
`xlab`	typical plot parameter: how the x axis is labelled, the default is "valorate LR".
`ylab`	typical plot parameter: how the y axis is labelled, the default is "density".
`main`	typical plot parameter. The default is an expression depending on the parameters.
`samp`	a numeric value specifying the length of sampling when using other density functions. It is related to the include argument.
`smooth`	the strength of density smoothing for display purposes. The default is 10.
`legends`	logical value that defines whether the legends for each curve should be displayed. The default is FALSE.
`shades`	define de colors used to shade the empirical distribution when the either 'vstat' argument is used or n1 represent the 'x' vector. The default is c(6,8).
`transparency`	defines the transparency in shades. The default is 0.25.
`lwd`	typical plot parameter: width of the lines. Default is 2.
`xlim`	typical plot parameter.
`minL,minR`	limits to the estimated empirical density.
`...`	arguments passed to plot.

Plots the estimated density of the log-rank distribution.

An invisible data frame of the density estimation.

Victor Trevino vtrevino@itesm.mx

Trevino et al. 2016 http://bioinformatica.mty.itesm.mx/valorateR

new.valorate. valorate.p.value. valorate.plot.empirical.

## Create a random population of 100 subjects 
## having 20 events
subjects <- numeric(100)
subjects[sample(100,20)] <- 1
vo <- new.valorate(rank=subjects, sampling.size=100000, verbose=TRUE)

groups <- numeric(100)
groups[sample(100,4)] <- 1  # only 4 subjects are within the 'mutated' group
pvr <- valorate.survdiff(vo, groups) 
print(pvr)

# Crude density
## Not run: valorate.plot.empirical(vo, 4)

# Similar but marking the statistic 
# returned by groups and shading
## Not run: valorate.plot.empirical(vo, groups)

# Plot density and check symmetry
## Not run: valorate.plot.empirical(vo, 4, 0)

# Now should be almost symmetric
## Not run: valorate.plot.empirical(vo, 50, 0)

# Crude density plus gaussian, weibull, and beta estimations
## Not run: valorate.plot.empirical(vo, 4, include="all", legends=TRUE)