rcModelPLMd: Fit robust row-column models to a matrix

In preprocessCore: A collection of pre-processing functions

Description

These functions fit row-column effect models to matrices using PLM-d

Usage

rcModelPLMd(y,group.labels)

Arguments

y	A numeric matrix
group.labels	A vector of group labels. Of length ncol(y)

Details

This functions first tries to fit row-column models to the specified input matrix. Specifically the model

y_ij = r_i + c_j + e_ij

with r_i and c_j as row and column effects respectively. Note that these functions treat the row effect as the parameter to be constrained using sum to zero.

Next the residuals for each row are compared to the group variable. In cases where there appears to be a significant relationship, the row-effect is "split" and separate row-effect parameters, one for each group, replace the single row effect.

Value

A list with following items:

Estimates	The parameter estimates. Stored in column effect then row effect order
Weights	The final weights used
Residuals	The residuals
StdErrors	Standard error estimates. Stored in column effect then row effect order
WasSplit	An indicator variable indicating whether or not a row was split with separate row effects for each group

Author(s)

B. M. Bolstad [e-mail]

See Also

rcModelPLM,rcModelPLMr

Examples

col.effects <- c(10,11,10.5,12,9.5)
row.effects <- c(seq(-0.5,-0.1,by=0.1),seq(0.1,0.5,by=0.1))


y <- outer(row.effects, col.effects,"+")
y <- y + rnorm(50,sd=0.1)

rcModelPLMd(y,group.labels=c(1,1,2,2,2))


row.effects <- c(4,3,2,1,-1,-2,-3,-4)
col.effects  <- c(8,9,10,11,12,10)

y <- outer(row.effects, col.effects,"+") + rnorm(48,0,0.25)

y[8,4:6] <- c(11,12,10)+ 2.5 + rnorm(3,0,0.25)
y[5,4:6] <- c(11,12,10)+-2.5 + rnorm(3,0,0.25)


rcModelPLMd(y,group.labels=c(1,1,1,2,2,2))

par(mfrow=c(2,2))
matplot(y,type="l",col=c(rep("red",3),rep("blue",3)),ylab="residuals",xlab="probe",main="Observed Data")
matplot(rcModelPLM(y)$Residuals,col=c(rep("red",3),rep("blue",3)),ylab="residuals",xlab="probe",main="Residuals (PLM)")
matplot(rcModelPLMd(y,group.labels=c(1,1,1,2,2,2))$Residuals,col=c(rep("red",3),rep("blue",3)),xlab="probe",ylab="residuals",main="Residuals (PLM-d)")

preprocessCore documentation built on Jan. 10, 2021, 2:01 a.m.