errorBar {EnvStats} | R Documentation |

## Plot Pointwise Error Bars

### Description

Plot pointwise error bars given their upper and lower limits.

The `errorBar`

function is a modified version of the S function
`error.bar`

. The EnvStats function `errorBar`

includes the
additional arguments `draw.lower`

, `draw.upper`

, `gap.size`

,
`bar.ends.size`

, and `col`

to determine whether both the lower and
upper error bars are drawn and to control the size of the gaps, the size of the bar
ends, and the color of the bars.

### Usage

```
errorBar(x, y = NULL, lower, upper, incr = TRUE, draw.lower = TRUE,
draw.upper = TRUE, bar.ends = TRUE, gap = TRUE, add = FALSE,
horizontal = FALSE, gap.size = 0.75, bar.ends.size = 1, col = 1,
..., xlab = deparse(substitute(x)), xlim, ylim)
```

### Arguments

`x` , `y` |
coordinates of points. The coordinates can be given by two vector arguments or by a
single vector When both When both If a single numeric vector is given, then Missing values ( |

`lower` |
pointwise lower limits of the error bars. This may be a single number or a vector
the same length as |

`upper` |
pointwise upper limits of the error bars. This may be a single number or a vector the
same length as |

`incr` |
logical scalar indicating whether the values in |

`draw.lower` |
logical scalar indicating whether to draw the lower error bar.
The default is |

`draw.upper` |
logical scalar indicating whether to draw the upper error bar.
The default is |

`bar.ends` |
logical scalar indicating whether flat bars should be drawn at the endpoints. The
default is |

`gap` |
logical scalar indicating whether gaps should be left around the points to emphasize
their locations. The default is |

`add` |
logical scalar indicating whether error bars should be added to the current plot.
If |

`horizontal` |
logical scalar indicating whether the error bars should be oriented horizontally
( |

`gap.size` |
numeric scalar controlling the width of the gap. |

`bar.ends.size` |
numeric scalar controlling the length of the bar ends. |

`col` |
numeric or character vector indicating the color(s) of the bars. |

`xlab` , `xlim` , `ylim` , `...` |
additional graphical parameters (see |

### Details

`errorBar`

creates a plot of `y`

versus `x`

with pointwise error bars.

### Value

`errorBar`

invisibly returns a list with the following components:

`group.centers` |
numeric vector of values on the group axis (the |

`group.stats` |
a matrix with the number of rows equal to the number of groups and three columns indicating the group location parameter (Center), the lower limit for the error bar (Lower), and the upper limit for the error bar (Upper). |

### Author(s)

Authors of S (for code for `error.bar`

in S).

Steven P. Millard (EnvStats@ProbStatInfo.com)

### References

Cleveland, W.S. (1994). *The Elements of Graphing Data*.
Hobart Press, Summit, New Jersey.

### See Also

`plot`

, `segments`

, `pointwise`

,
`stripChart`

.

### Examples

```
# The guidance document USEPA (1994b, pp. 6.22--6.25)
# contains measures of 1,2,3,4-Tetrachlorobenzene (TcCB)
# concentrations (in parts per billion) from soil samples
# at a Reference area and a Cleanup area. These data are strored
# in the data frame EPA.94b.tccb.df.
#
# Using the log-transformed data, create
#
# 1. A dynamite plot (bar plot showing mean plus 1 SE)
#
# 2. A confidence interval plot.
TcCB.mat <- summaryStats(TcCB ~ Area, data = EPA.94b.tccb.df,
se = TRUE, ci = TRUE)
Means <- TcCB.mat[, "Mean"]
SEs <- TcCB.mat[, "SE"]
LCLs <- TcCB.mat[, "95%.LCL"]
UCLs <- TcCB.mat[, "95%.UCL"]
# Dynamite Plot
#--------------
dev.new()
group.centers <- barplot(Means, col = c("red", "blue"),
ylim = range(0, Means, Means + SEs), ylab = "TcCB (ppb)",
main = "Dynamite Plot for TcCB Data")
errorBar(x = as.vector(group.centers), y = Means,
lower = SEs, draw.lower = FALSE, gap = FALSE,
col = c("red", "blue"), add = TRUE)
# Confidence Interval Plot
#-------------------------
xlim <- par("usr")[1:2]
dev.new()
errorBar(x = as.vector(group.centers), y = Means,
lower = LCLs, upper = UCLs, incr = FALSE, gap = FALSE,
col = c("red", "blue"), xlim = xlim, xaxt = "n",
xlab = "", ylab = "TcCB (ppb)",
main = "Confidence Interval Plot for TcCB Data")
axis(1, at = group.centers, labels = dimnames(TcCB.mat)[[1]])
# Clean up
#---------
rm(TcCB.mat, Means, SEs, LCLs, UCLs, group.centers, xlim)
graphics.off()
```

*EnvStats*version 2.8.1 Index]