lvplot.rrvglm(object, A = TRUE, C = TRUE, scores = FALSE, show.plot = TRUE, groups = rep(1, n), gapC = sqrt(sum(par()$cxy^2)), scaleA = 1, xlab = "Latent Variable 1", ylab = "Latent Variable 2", Alabels = if (length(object@misc$predictors.names)) object@misc$predictors.names else paste("LP", 1:M, sep = ""), Aadj = par()$adj, Acex = par()$cex, Acol = par()$col, Apch = NULL, Clabels = rownames(Cmat), Cadj = par()$adj, Ccex = par()$cex, Ccol = par()$col, Clty = par()$lty, Clwd = par()$lwd, chull.arg = FALSE, ccex = par()$cex, ccol = par()$col, clty = par()$lty, clwd = par()$lwd, spch = NULL, scex = par()$cex, scol = par()$col, slabels = rownames(x2mat), ...)
"rrvglm"
. TRUE
then
C is represented by arrows emenating from the origin. FALSE
, no plot is produced
and the matrix of scores ($n$ latent variable values) is returned.
If TRUE
, the rank of object
need not be 2.
multinomial
.par
. par
. adj
argument of par
. cex
argument of par
. col
argument of par
. par
.
The pch
argument can be of length $M$, the number of species. adj
argument of par
. cex
argument of par
. col
argument of par
. lty
argument of par
. lwd
argument of par
. group
argument). cex
argument of par
. col
argument of par
. lty
argument of par
. lwd
argument of par
. par
.
The spch
argument can be of length $M$, the number of species. cex
argument of par
. col
argument of par
. plot
function
when setting up the entire plot. Useful arguments here include
xlim
and ylim
.
length(unique(groups))
),
and ``s'' to scores (of length $n$).As the result is a biplot, its interpretation is based on the inner product.
Yee, T. W. and Hastie, T. J. (2003) Reduced-rank vector generalized linear models. Statistical Modelling, 3, 15--41.
lvplot
,
par
,
rrvglm
,
Coef.rrvglm
,
rrvglm.control
.
nn <- nrow(pneumo) # x1, x2 and x3 are some unrelated covariates
pneumo <- transform(pneumo, slet = scale(log(exposure.time)),
x1 = rnorm(nn), x2 = rnorm(nn), x3 = rnorm(nn))
fit <- rrvglm(cbind(normal, mild, severe) ~ slet + x1 + x2 + x3,
multinomial, data = pneumo, Rank = 2,
Corner = FALSE, Uncorrel = TRUE)
## Not run:
# lvplot(fit, chull = TRUE, scores = TRUE, clty = 2, ccol = "blue",
# scol = "red", Ccol = "darkgreen", Clwd = 2, Ccex = 2,
# main = "Biplot of some fictitional data") ## End(Not run)
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