plotvgam {VGAM} | R Documentation

## Default VGAM Plotting

### Description

Component functions of a `vgam-class` object can be plotted with `plotvgam()`. These are on the scale of the linear/additive predictor.

### Usage

    plotvgam(x, newdata = NULL, y = NULL, residuals = NULL,
             rugplot = TRUE, se = FALSE, scale = 0, raw = TRUE,
             offset.arg = 0, deriv.arg = 0, overlay = FALSE,
             type.residuals = c("deviance", "working", "pearson", "response"),
             plot.arg = TRUE, which.term = NULL, which.cf = NULL,
             control = plotvgam.control(...), varxij = 1, ...)

### Arguments

`x` | A fitted VGAM object, e.g., produced by `vgam`, `vglm`, or `rrvglm`.
`newdata` | Data frame. May be used to reconstruct the original data set.
`y` | Unused.
`residuals` | Logical. If `TRUE` then residuals are plotted. See `type.residuals`
`rugplot` | Logical. If `TRUE` then a rug plot is plotted at the foot of each plot. These values are jittered to expose ties.
`se` | Logical. If `TRUE` then approximate +-2 pointwise standard error bands are included in the plot.
`scale` | Numerical. By default, each plot will have its own y-axis scale. However, by specifying a value, each plot's y-axis scale will be at least `scale` wide.
`raw` | Logical. If `TRUE` then the smooth functions are those obtained directly by the algorithm, and are plotted without having to premultiply with the constraint matrices. If `FALSE` then the smooth functions have been premultiply by the constraint matrices. The `raw` argument is directly fed into `predict.vgam()`.
`offset.arg` | Numerical vector of length r. These are added to the component functions. Useful for separating out the functions when `overlay` is `TRUE`. If `overlay` is `TRUE` and there is one covariate then using the intercept values as the offsets can be a good idea.
`deriv.arg` | Numerical. The order of the derivative. Should be assigned an small integer such as 0, 1, 2. Only applying to `s()` terms, it plots the derivative.
`overlay` | Logical. If `TRUE` then component functions of the same covariate are overlaid on each other. The functions are centered, so `offset.arg` can be useful when `overlay` is `TRUE`.
`type.residuals` | if `residuals` is `TRUE` then the first possible value of this vector, is used to specify the type of residual.
`plot.arg` | Logical. If `FALSE` then no plot is produced.
`which.term` | Character or integer vector containing all terms to be plotted, e.g., `which.term = c("s(age)", "s(height"))` or `which.term = c(2, 5, 9)`. By default, all are plotted.
`which.cf` | An integer-valued vector specifying which linear/additive predictors are to be plotted. The values must be from the set {1,2,...,r}. By default, all are plotted.
`control` | Other control parameters. See `plotvgam.control`.
`...` | Other arguments that can be fed into `plotvgam.control`. This includes line colors, line widths, line types, etc.
`varxij` | Positive integer. Used if `xij` of `vglm.control` was used, this chooses which inner argument the component is plotted against. This argument is related to `raw = TRUE` and terms such as `NS(dum1, dum2)` and constraint matrices that have more than one column. The default would plot the smooth against `dum1` but setting `varxij = 2` could mean plotting the smooth against `dum2`. See the VGAM website for further information.

### Details

In this help file M is the number of linear/additive predictors, and r is the number of columns of the constraint matrix of interest.

Many of `plotvgam()`'s options can be found in `plotvgam.control`, e.g., line types, line widths, colors.

### Value

The original object, but with the `preplot` slot of the object assigned information regarding the plot.

### Note

While `plot(fit)` will work if `class(fit)` is `"vgam"`, it is necessary to use `plotvgam(fit)` explicitly otherwise.

`plotvgam()` is quite buggy at the moment.

### Author(s)

Thomas W. Yee

### See Also

`vgam`, `plotvgam.control`, `predict.vgam`, `plotvglm`, `vglm`.

### Examples

    coalminers <- transform(coalminers, Age = (age - 42) / 5)
    fit <- vgam(cbind(nBnW, nBW, BnW, BW) ~ s(Age),
                binom2.or(zero = NULL), data = coalminers)
    ## Not run:  par(mfrow = c(1,3))
    plot(fit, se = TRUE, ylim = c(-3, 2), las = 1)
    plot(fit, se = TRUE, which.cf = 1:2, lcol = "blue", scol = "orange",
         ylim = c(-3, 2))
    plot(fit, se = TRUE, which.cf = 1:2, lcol = "blue", scol = "orange",
         overlay = TRUE)
    ## End(Not run)

[Package VGAM version 1.0-3 Index]