apc (version 2.0.0)

apc.plot.fit.pt: Plot probability transform of responses given fitted values

Description

Constructs probability transforms of responses given fitted values from apc.fit.model. The plot is given in the original coordinate system. Colours and symbols are used to indicate whether responses are central to the fitted distribution or in the tails of the fitted distribution.

Usage

apc.plot.fit.pt(apc.fit.model,
					   do.plot=TRUE,do.value=FALSE,
					   pch=c(21,24,25),
					   col=c("black","green","blue","red"),
					   bg=NULL,cex=NULL,main=NULL)

Arguments

apc.fit.model

List. See apc.fit.model for a description of the format.

do.plot

Optional. Logical. If FALSE plot is not produced. Default is TRUE.

do.value

Optional. Logical. If TRUE value is produced. Default is FALSE.

pch

Optional points argument. Numeric. Default is 21/24/25. 21 is a circle used for the central 80% of distribution. 24/25 are triangle point up/down used for right tail and left tail.

col

Optional plot argument. Character or Numeric. Default is "black"/"green"/"blue"/"red". Black is use for central 80%, Green is used for 90-95% and 5-10%, Blue is used for 95-99% and 1-5%, Red is used for tails.

bg

Optional plot argument. Character or Numeric. Default is bg=col.

cex

Optional plot argument. Numeric. Magnification. Default is internally computed.

main

Optional plot argument. Character. Main title. Default is internally computed.

Value

Vector of probability transforms. Only produced if do.value is set to TRUE. See example below.

See Also

data.Italian.bladder.cancer for information on the data used in the example.

Examples

# NOT RUN {
#####################
#	Example with Italian bladder cancer data
#	HOW TO USE VALUE

data.list	<- data.Italian.bladder.cancer()
fit			<- apc.fit.model(data.list,"poisson.dose.response","APC")
v.pt		<- apc.plot.fit.pt(fit,do.value=TRUE)
m.pt		<- matrix(data=NA,nrow=fit$data.xmax,ncol=fit$data.ymax)
m.pt[fit$index.data]	<- v.pt
m.pt

#	            [,1]      [,2]       [,3]       [,4]      [,5]
#	 [1,] 0.63782311 0.5651585 0.33982477 0.91299734 0.5759652
#	 [2,] 0.82676269 0.8992667 0.26378120 0.28795884 0.3708787
#	 [3,] 0.54139571 0.2445995 0.51923747 0.63451773 0.7955547
#	 [4,] 0.87364488 0.8228499 0.07219437 0.38789788 0.5938305
#	 [5,] 0.86797473 0.3934085 0.34525271 0.38955656 0.5097203
#	 [6,] 0.65027598 0.8377994 0.29018594 0.03694977 0.7990229
#	 [7,] 0.43769468 0.1099946 0.50261364 0.56777485 0.8916552
#	 [8,] 0.67518708 0.5519831 0.67817803 0.19793887 0.5354669
#	 [9,] 0.02717016 0.2066092 0.77035122 0.89047749 0.5017919
#	[10,] 0.71037782 0.9464356 0.36897847 0.41790169 0.2080577
#	[11,] 0.50922468 0.3085978 0.55261186 0.77592343 0.3597815
# }