bandplot {gplots} R Documentation

## Plot x-y Points with Locally Smoothed Mean and Standard Deviation

### Description

Plot x-y Points with lines showing the locally smoothed mean and standard deviation.

### Usage

```  bandplot(x, y, ..., add = FALSE, sd = c(-2:2),
sd.col=c("magenta", "blue", "red", "blue", "magenta"),
sd.lwd=c(2, 2, 3, 2, 2),  sd.lty=c(2, 1, 1, 1, 2),
method = "frac", width = 1/5, n=50)
```

### Arguments

 `x` numeric vector of x locations `y` numeric vector of x locations `...` Additional plotting parameters. `add` Boolean indicating whether the local mean and standard deviation lines should be added to an existing plot. Defaults to FALSE. `sd` Vector of multiples of the standard devation that should be plotted. `0` gives the mean, `-1` gives the mean minus one standard deviation, etc. Defaults to -2:2. `sd.col,sd.lwd,sd.lty` Color, line width, and line type of each plotted line. `method, width, n` Parameters controlling the smoothing. See the help page for `wapply` for details.

### Details

`bandplot` was created to look for changes in the mean or variance of scatter plots, particularly plots of regression residuals.

The local mean and standard deviation are calculated by calling 'wapply'. By default, bandplot asks wapply to smooth using intervals that include the nearest 1/5 of the data. See the documentation of that function for details on the algorithm.

### Value

Invisibly returns a list containing the x,y points plotted for each line.

### Author(s)

Gregory R. Warnes greg@warnes.net

`lowess`

### Examples

```
# fixed mean, changing variance
x <- 1:1000
y <- rnorm(1000, mean=1, sd=1 + x/1000 )
bandplot(x,y)

# fixed varance, changing mean
x <- 1:1000
y <- rnorm(1000, mean=x/1000, sd=1)
bandplot(x,y)

#
# changing mean and variance
#
x <- abs(rnorm(500))
y <- rnorm(500, mean=2*x, sd=2+2*x)

# the changing mean and dispersion are hard to see whith the points alone:
plot(x,y )

# regression picks up the mean trend, but not the change in variance
reg <- lm(y~x)
summary(reg)

# using bandplot on the original data helps to show the mean and
# variance trend
bandplot(x,y)

# using bandplot on the residuals helps to see that regression removes
# the mean trend but leaves the trend in variability
bandplot(predict(reg),resid(reg))

```

[Package gplots version 2.11.0 Index]