plot-methods {acs} | R Documentation

## acs Methods for Function `plot`

### Description

Plot acs objects, with both estimates and confidence intervals.

### Usage

    ## S4 method for signature 'acs'
    plot(x, conf.level=.95, err.col="red", err.lwd=1,
    err.pch="-", err.cex=2, err.lty=2, x.res=300, labels="auto",
    by="geography", true.min=T, ...)

### Arguments

`x` | the acs object to be plotted
`conf.level` | the desired confidence interval to use for error bars; numeric between 0<1
`err.col` | the color to use for the error bars; analogous to graphic parameter `col`
`err.lwd` | the line weight to use for the error bars; analogous to graphic parameter `lwd`
`err.pch` | the point character to use for the error bars; analogous to graphic parameter `pch`
`err.cex` | the scaling factor to use for the error bars; analogous to graphic parameter `cex`
`err.lty` | the line type to use for the error bars; analogous to graphic parameter `lty`
`x.res` | when plot called with a single acs value (see below), x.res determines the resolution of the resulting density plot; integer (defaults to 300, i.e., the curve is drawn with 300 points)
`labels` | the labels to use for the x axis; defaults to either geography names or acs.colnames based on dimensions of object plotted; vector of proper length required
`by` | in cases where multiple rows and columns are plotted, whether to provide a different plot for each value of `geography` (the default) or `acs.colnames`; accepts either "geography" or "acs.colnames"
`true.min` | whether to limit the lower bound of a confidence interval to some value or now; `TRUE` (the default) allows for negative lower bounds; also accepts `FALSE` to limit lower bounds to 0, or any number, to use that as a minimum lower bound; see details.
`...` | provided to allow for passing of additional arguments to plot functions

### Methods

`signature(object = "acs")`

  When passed an acs object (possibly involving subsetting), `plot` will call a plot showing both estimates and confidence intervals for the data contained in the object.

  If the object contains only one row or only one column, `plot` will use this dimension as the y-axis and will plot each observation along the x-axis, as three points (an estimate bracketed by upper and lower confidence bounds). If the object contains multiple rows and columns, `plot` will return a 1-by-y "plot of plots": by default there will be one plot per row showing all the data for each geography, although this can be changed by specifying `by="acs.colnames"`, to plot each variable as its own plot, with all of the geographies along the x-axis.

  In the special case where the dimensions of the object are exactly c(1,1) (i.e., a single geography and column), `plot` will return a density plot of the estimate. In this case, `conf.level`, `err.col`, `err.lty`, and `err.lwd` will be used to determine the properties of the margins of error lines. (For none, use `conf.level=F`. For these density plots, users may also wish to set `xlim` and `x.res`, which specify the horizontal extent and resolution of the plot.)

  `plot` accepts many of the standard graphical arguments to `plot`, such as `main`, `sub`, `xlab`, `pch`, and `col`, as well new ones listed above.

  In some cases, the lower bound of a confidence interval may extend below 0; in some cases this is desired, especially when a variable is actually stating the difference between two estimates. In other cases, this may seem confusing (for example, when reporting the estimated count in a particular category). Setting `true.min` to `FALSE` (or 0) will limit the lower boundary of any confidence intervals computed and plotted.

### Examples

    # load ACS data
    data(kansas07)

    # plot a single value
    plot(kansas07[4,4])

    # plot by geography
    plot(kansas07[,10])

    # plot by columns
    plot(kansas07[4,3:10])

    # a density plot for a single variable
    plot(kansas07[7,10])

    # same, using some graphical parameters
    plot(kansas07[7,10], col="blue", err.col="purple", err.lty=3)

    plot(kansas07[7,49], col="lightblue", type="h", x.res=3000,
    err.col="purple", err.lty=3, err.lwd=4, conf.level=.99,
    main=(paste("Distribution of Females>85 Years in ",
    geography(kansas07)[7,1], sep="")),
    sub="(99-percent margin of error shown in purple)")

    # something more complicated...

    plot(kansas07[c(1,3,4),3:25], err.col="purple",
    pch=16, err.pch="x", err.cex=1, ylim=c(0,5000),
    col=rainbow(23), conf.level=.99,
    labels=paste("grp. ",1:23))

[Package acs version 2.1.4 Index]