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. \dots 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 1.48.0 Index]