bootMeans: Bin data, calculate mean and bootstrap confidence interval in...

In openair: Tools for the Analysis of Air Pollution Data

Bin data, calculate mean and bootstrap confidence interval in the mean

Description

binData() summarises data by intervals and calculates the mean and bootstrap confidence intervals (by default 95% CI) in the mean of a chosen variable in a data frame. Any other numeric variables are summarised by their mean intervals. This occurs via bootMeanDF(), which calculates the uncertainty intervals in the mean of a vector.

Usage

binData(
  mydata,
  bin = "nox",
  uncer = "no2",
  type = "default",
  n = 40,
  interval = NA,
  breaks = NA,
  conf.int = 0.95,
  B = 250,
  ...
)

bootMeanDF(x, conf.int = 0.95, B = 1000)

Arguments

mydata	Name of the data frame to process.
bin	The name of the column to divide into intervals.
uncer	The name of the column for which the mean, lower and upper uncertainties should be calculated for each interval of bin.
type	Used for splitting the data further. Passed to cutData(). Note that intervals are calculated on the whole dataset before the data is categorised, meaning intervals will be the same for the different groups.
n	The number of intervals to split bin into.
interval	The interval to be used for binning the data.
breaks	User specified breaks to use for binning.
conf.int	The confidence interval, defaulting to 0.95 (i.e., the 95% Confidence Interval).
B	The number of bootstrap simulations.
...	Passed to cutData() for use with type.
x	A vector from which the mean and bootstrap confidence intervals in the mean are to be calculated

Details

There are three options for binning. The default is to bin bin into 40 intervals. Second, the user can choose an binning interval, e.g., interval = 5. Third, the user can supply their own breaks to use as binning intervals. Note that intervals are calculated on the whole dataset before the data is cut into categories using type.

Value

Returns a summarised data frame with new columns for the mean and upper / lower confidence intervals in the mean.

Examples

# work with vectors
test <- rnorm(20, mean = 10)
bootMeanDF(test)

# how does nox vary by intervals of wind speed?
results <- binData(mydata, bin = "ws", uncer = "nox")
## Not run: 
library(ggplot2)
ggplot(results, aes(x = ws, y = mean, ymin = min, ymax = max)) +
  geom_pointrange()

## End(Not run)

# what about weekend vs weekday?
results2 <- binData(mydata, bin = "ws", uncer = "nox", type = "weekend")
## Not run: 
ggplot(results2, aes(x = ws, y = mean, ymin = min, ymax = max)) +
  geom_pointrange() +
  facet_wrap(vars(weekend))

## End(Not run)

openair documentation built on April 2, 2026, 9:07 a.m.