Fit row-column model to a matrix
These functions fit row-column effect models to matrices
subrcModelPLM(y, group.labels,row.effects=NULL,input.scale=NULL) subrcModelMedianPolish(y, group.labels)
y |
A numeric matrix |
group.labels |
A vector to be treated as a factor variable. This is used to assign each row to a group. NA values should be used to exclude rows from consideration |
row.effects |
If these are supplied then the fitting procedure uses these (and analyzes individual columns separately) |
input.scale |
If supplied will be used rather than estimating the scale from the data |
These functions 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 this functions treat the row effect as
the parameter to be constrained using sum to zero (for
rcModelPLM and rcModelWPLM) or median of zero (for
rcModelMedianPolish).
The rcModelPLM and rcModelWPLM functions use a
robust linear model procedure for fitting the model.
The function rcModelMedianPolish uses the median polish algorithm.
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 |
Scale |
Scale Estimates |
B. M. Bolstad bmb@bmbolstad.com
y <- matrix(c(10+rnorm(50),20+rnorm(50)),20,5,byrow=TRUE) subrcModelPLM(y,c(rep(1,10),rep(2,10))) subrcModelMedianPolish(y,c(rep(1,10),rep(2,10))) 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,"+") w <- runif(50) rcModelPLM(y) rcModelWPLM(y, w) rcModelMedianPolish(y) y <- y + rnorm(50) rcModelPLM(y) rcModelWPLM(y, w) rcModelMedianPolish(y) rcModelPLM(y,row.effects=row.effects) rcModelWPLM(y,w,row.effects=row.effects) rcModelPLM(y,input.scale=1.0) rcModelWPLM(y, w,input.scale=1.0) rcModelPLM(y,row.effects=row.effects,input.scale=1.0) rcModelWPLM(y,w,row.effects=row.effects,input.scale=1.0)
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