Function to create an array of time series across accrual lags using the running median

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Description

Creates an array of time series graphs–one for each accrual lag–and displays a running median and MAD-based bounds on each graph.

Usage

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laggedTSarray(x, daysOfHistory, lags, ...)

Arguments

x

Object of the accrued class containing data to be plotted.

daysOfHistory

An integer greater or equal to 1. If NULL, then defaults to 30. The number of days of previous data used to calculate the running median.

lags

A vector of nonnegative integers specifying which lagged time series will be plotted. If NULL, all lags are used.

...

Parameters to pass to plot.

Details

An array of graphs is produced, with the ith graph showing for each encounter date the cumulative counts received i-1 days after the encounter date, with the final graph showing the final counts. A running median and error bars are disiplayed by default. Error bars are calculated as \pm (2)(MAD) (median absolute deviations) from the running median, calculated using the same running window.

Value

None.

Author(s)

Julie Eaton and Ian Painter

See Also

data.accrued, stackedUploadData, uploadPattern, plot.accrued, plot.summary.accrued, lagHistogram, asOf

Examples

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	data(accruedDataExample)			# simulated accrued data
	dat <- data.accrued(accruedDataExample)	# Convert to data.accrued object
	laggedTSarray(dat)