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While I like the n.plot option in plot.gllvm(), it seems that it might be worth having a var.subset option similar to plot.manyglm() that allows the column index of a response variable to be specified. I've noticed that by default, when n.plot = 2 and the residuals of model are plotted, it seems the 2 response variables chosen are random (and it seems to be random no matter what the value of n.plot is. I know I can always extract the residuals and plot them myself (that's what I'm currently doing), but I figured I'd suggest anyways.
# First run ####
model |> plot(which = 1, n.plot = 2)
# Second run ####
model |> plot(which = 1, n.plot = 2)
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Hi folks,
While I like the
n.plot
option inplot.gllvm()
, it seems that it might be worth having avar.subset
option similar toplot.manyglm()
that allows the column index of a response variable to be specified. I've noticed that by default, whenn.plot = 2
and the residuals of model are plotted, it seems the 2 response variables chosen are random (and it seems to be random no matter what the value ofn.plot
is. I know I can always extract the residuals and plot them myself (that's what I'm currently doing), but I figured I'd suggest anyways.Beta Was this translation helpful? Give feedback.
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