calcPercentile: Calculate percentile values from a time series
In davidcarslaw/ggopenair: Tools for the Analysis of Air Pollution Data

Description Usage Arguments Details Value Author(s) See Also Examples

Calculates multiple percentile values from a time series, with flexible time aggregation.

1 2	calcPercentile(mydata, pollutant = "o3", avg.time = "month", percentile = 50, data.thresh = 0, start = NA)

`mydata`	A data frame of data with a `date` field in the format `Date` or `POSIXct`. Must have one variable to apply calculations to.
`pollutant`	Name of variable to process. Mandatory.
`avg.time`	Averaging period to use. See `timeAverage` for details.
`percentile`	A vector of percentile values. For example `percentile = 50` for median values, `percentile = c(5, 50, 95` for multiple percentile values.
`data.thresh`	Data threshold to apply when aggregating data. See `timeAverage` for details.
`start`	Start date to use - see `timeAverage` for details.

This is a utility function to calculate percentiles and is used in, for example, timePlot. Given a data frame with a date field and one other numeric variable, percentiles are calculated.

Returns a data frame with new columns for each percentile level. New columns are given names like percentile.95 e.g. when percentile = 95 is chosen. See examples below.

David Carslaw

timePlot, timeAverage

# 95th percentile monthly o3 concentrations
percentiles <- calcPercentile(mydata, pollutant ="o3",
avg.time = "month", percentile = 95)

head(percentiles)

# 5, 50, 95th percentile monthly o3 concentrations
## Not run: 
percentiles <- calcPercentile(mydata, pollutant ="o3",
avg.time = "month", percentile = c(5, 50, 95))

head(percentiles)

## End(Not run)