VGAM: lvplot.rrvglm – R documentation

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lvplot.rrvglm

Latent Variable Plot for RR-VGLMs

Description

Produces an ordination diagram (also known as a biplot or latent variable plot) for reduced-rank vector generalized linear models (RR-VGLMs). For rank-2 models only, the x- and y-axis are the first and second canonical axes respectively.

Usage

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$predictors.names else param.names("LP", M),
              Aadj = par()$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), ...)

Arguments

`object`	Object of class `"rrvglm"`.
`A`	Logical. Allow the plotting of A?
`C`	Logical. Allow the plotting of C? If `TRUE` then C is represented by arrows emenating from the origin.
`scores`	Logical. Allow the plotting of the n scores? The scores are the values of the latent variables for each observation.
`show.plot`	Logical. Plot it? If `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.
`groups`	A vector whose distinct values indicate which group the observation belongs to. By default, all the observations belong to a single group. Useful for the multinomial logit model (see `multinomial`.
`gapC`	The gap between the end of the arrow and the text labelling of C, in latent variable units.
`scaleA`	Numerical value that is multiplied by A, so that C is divided by this value.
`xlab`	Caption for the x-axis. See `par`.
`ylab`	Caption for the y-axis. See `par`.
`Alabels`	Character vector to label A. Must be of length M.
`Aadj`	Justification of text strings for labelling A. See the `adj` argument of `par`.
`Acex`	Numeric. Character expansion of the labelling of A. See the `cex` argument of `par`.
`Acol`	Line color of the arrows representing C. See the `col` argument of `par`.
`Apch`	Either an integer specifying a symbol or a single character to be used as the default in plotting points. See `par`. The `pch` argument can be of length M, the number of species.
`Clabels`	Character vector to label C. Must be of length p2.
`Cadj`	Justification of text strings for labelling C. See the `adj` argument of `par`.
`Ccex`	Numeric. Character expansion of the labelling of C. See the `cex` argument of `par`.
`Ccol`	Line color of the arrows representing C. See the `col` argument of `par`.
`Clty`	Line type of the arrows representing C. See the `lty` argument of `par`.
`Clwd`	Line width of the arrows representing C. See the `lwd` argument of `par`.
`chull.arg`	Logical. Plot the convex hull of the scores? This is done for each group (see the `group` argument).
`ccex`	Numeric. Character expansion of the labelling of the convex hull. See the `cex` argument of `par`.
`ccol`	Line color of the convex hull. See the `col` argument of `par`.
`clty`	Line type of the convex hull. See the `lty` argument of `par`.
`clwd`	Line width of the convex hull. See the `lwd` argument of `par`.
`spch`	Either an integer specifying a symbol or a single character to be used as the default in plotting points. See `par`. The `spch` argument can be of length M, the number of species.
`scex`	Numeric. Character expansion of the labelling of the scores. See the `cex` argument of `par`.
`scol`	Line color of the arrows representing C. See the `col` argument of `par`.
`slabels`	Character vector to label the scores. Must be of length n.
`...`	Arguments passed into the `plot` function when setting up the entire plot. Useful arguments here include `xlim` and `ylim`.

Details

For RR-VGLMs, a biplot and a latent variable plot coincide. In general, many of the arguments starting with “A” refer to A (of length M), “C” to C (of length p2), “c” to the convex hull (of length length(unique(groups))), and “s” to scores (of length n).

As the result is a biplot, its interpretation is based on the inner product.

Value

The matrix of scores (n latent variable values) is returned regardless of whether a plot was produced or not.

Note

The functions lvplot.rrvglm and biplot.rrvglm are equivalent.

In the example below the predictor variables are centered, which is a good idea.

Author(s)

Thomas W. Yee

References

Yee, T. W. and Hastie, T. J. (2003). Reduced-rank vector generalized linear models. Statistical Modelling, 3, 15–41.

Examples

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)

VGAM

Vector Generalized Linear and Additive Models

v1.1-5

GPL-3

Authors

Thomas Yee [aut, cre], Cleve Moler [ctb] (author of several LINPACK routines)

Initial release

2021-01-13