plotBins {HELP} | R Documentation

## Plot bins

### Description

Plot densities of multiple bins of data, divided by a sliding window approach

### Usage

    plotBins(x, y, ...)

### Arguments

`x` | the vector of numerical data to be plotted. If `x` is a matrix it is interpreted as a vector. `x` can also be of class `"ExpressionSet"`.
`y` | an additional vector of numerical data to be used for binning. If `y` is a matrix it is interpreted as a vector. `y` can also be of class `"ExpressionSet"`.
`...` | Arguments to be passed to methods (see `plotBins-methods`): `element` which element of `AssayData` to use for a given `ExpressionSet` input (default is "exprs") `sample` which element of `sampleNames` to use as data (default is 1). Can be a character matching a sample name or simply an integer indicating which sample to choose. See `getSamples`. `feature` which element of `featureData` to use as binning variable (default is 1). Can be a character matching `varLabel` or simply an integer indicating which feature to choose. See `getFeatures`. `num.bins` number of bins (default is 10) used to divide the data `num.steps` number of steps (default is 3) used to create bin offsets, resulting in bins of sliding windows `mode` the binning mode to be used. This must be either "continuous" or "discrete". "continuous" mode will divide the data into density-dependent bins. "discrete" mode will divide the data uniformly by binning data values. `show.avg` logical; if TRUE, plots overall density in addition to densities per bin. If FALSE (default), overall density plot is omitted. `main` an overall title for the plot: see `title`. `xlab` a title for the x axis: see `title`. `ylab` a title for the y axis: see `title`. `na.rm` logical; if TRUE (default), missing values are removed from x and y. If FALSE any missing values cause an error. `...` other arguments to be passed to `plot`. See `plot`.

### Author(s)

Reid F. Thompson (rthompso@aecom.yu.edu)

### See Also

`plotBins-methods`, `density`, `quantile`

### Examples

    #demo(pipeline,package="HELP")

    x <- 1:1000
    y <- sample(1:50,size=1000,replace=TRUE)
    plotBins(x,y,show.avg=TRUE,main="Random binning data",xlab="1:1000")

    #rm(x,y)

[Package HELP version 1.0.0 Index]