Fit row-column model to a matrix
These functions fit row-column effect models to matrices
rcModelPLM(y,row.effects=NULL,input.scale=NULL) rcModelWPLM(y, w,row.effects=NULL,input.scale=NULL) rcModelMedianPolish(y)
y |
A numeric matrix |
w |
A matrix or vector of weights. These should be non-negative. |
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
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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