Plot fitted model and standardised residuals for a multiscan object

Description

This function provides plots for fitted model and standardised residual for multiscan fitted objects.

Usage

## S3 method for class 'multiscan'
plot(x, residual=FALSE,...)

Arguments

Details

Fitted model on the input data, after rescaling by the corresponding scanning effects, is plotted against the estimated gene expressions. Standardised residuals for each scan of data are plotted against the rank of estimated gene expressions.

Value

Returns either one plot of the fitted model (residual=FALSE) on the input data or m plots of the residuals (residual=TRUE) corresponding to each scan of data.

References

Khondoker, M. R., Glasbey, C. A. and Worton, B. J. (2006). Statistical estimation of gene expression using multiple laser scans of microarrays. Bioinformatics 22, 215–219.

See Also

multiscan

Examples

data(murine)

fit<-multiscan(murine)

## plot the fitted model

plot(fit)

## plot the residuals

op<-par(mfrow=c(2,2))
plot(fit, residual=TRUE)
par(op)

Results

R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(multiscan)
*** Loaded multiscan Version 1.32.0 *** 
Type 'vignette("multiscan")' to view the package vignette.
> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/multiscan/plot.multiscan.Rd_%03d_medium.png", width=480, height=480)
> ### Name: plot.multiscan
> ### Title: Plot fitted model and standardised residuals for a multiscan
> ###   object
> ### Aliases: plot.multiscan
> ### Keywords: regression
> 
> ### ** Examples
> 
> 
> data(murine)
> 
> fit<-multiscan(murine)

Estimating 1000 gene expressions using 4 scans of data
------------------------------------------------------------
Log-likelihood at initial parameters:  -21348.7187
------------------------------------------------------------
End of global iteration: 1, Log-likelihood:   -19542.94736
End of global iteration: 2, Log-likelihood:   -19373.08458
End of global iteration: 3, Log-likelihood:   -19351.64478
End of global iteration: 4, Log-likelihood:   -19349.44816
End of global iteration: 5, Log-likelihood:   -19348.63585
End of global iteration: 6, Log-likelihood:   -19348.63585
> 
> ## plot the fitted model
> 
> plot(fit)
> 
> ## plot the residuals
> 
> op<-par(mfrow=c(2,2))
> plot(fit, residual=TRUE)
> par(op)
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>