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

In apc: Age-Period-Cohort Analysis

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.

Author(s)

Bent Nielsen <[e-mail]> 2 Dec 2013

See Also

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

Examples

#####################
#	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

Example output

            [,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

apc documentation built on Oct. 23, 2020, 6:17 p.m.