Bin averaging

Average a vector into bins.

Usage

AvgToBin(x, y, N = 2, breaks = pretty(x, N), right = TRUE, bFill = FALSE)

Arguments

x

vector of values on which the data in y is tabulated; e.g. depth or time points.

y

vector of observation values to be averaged into bins. Must have the same length as x.

N

desired number of breaks (ignored if breaks are supplied directly).

breaks

vector of break point positions to define the averagig bins; if omitted, break point positions are calculated from the range of x and the desired number of breaks given by N.

right

logical; indicate whether the bin intervals should be closed on the right and open on the left (TRUE, the default), or vice versa (FALSE).

bFill

logical; if TRUE, fill empty bins using linear interpolation from the neighbours to the center of the bin.

Value

a list with four elements:

breaks:

numeric vector of the used break point positions.

centers:

numeric vector with the positions of the bin centers.

avg:

numeric vector with the bin-averaged values.

nobs:

numeric vector with the number of observations contributing to each bin average.

Details

This function averages the vector y into bins according to the positon of x within the breaks. You can either specify a desired number N of breaks which are used to calculate the actual breaks via pretty(x, N), or directly specify the N + 1 break positions. For right = TRUE (the default) the averaging bins are defined via x > breaks[i] and x <= breaks[i + 1], else they are defined via x >= breaks[i] and x < breaks[i + 1]. If bFill = TRUE, empty bins are filled using linear interpolation from the neighbours to the center of the bin.

Probably the binning could be considerably speeded up by using ?cut.

Author

Thomas Laepple

Examples

N <- 100
x1 <- seq(1, N, by = 1)
y1 <- SimPLS(N, a = 0.1, b = 1)
plot(x1, y1, type = "l")

y2 <- AvgToBin(x1, y1, 13)
lines(y2$centers, y2$avg, col = "green")


#Add some NA values to the timeseries
y1[(N/2):(N/2 +5)] <- NA
plot(x1, y1, type = "l")

y2 <- AvgToBin(x1, y1, 25)
lines(y2$centers, y2$avg, col = "green")

# Large enough bins will average across the gap
y3 <- AvgToBin(x1, y1, 10)
lines(y3$centers, y3$avg, col = "red")
# Or interpolate to nearest neighbour
y3 <- AvgToBin(x1, y1, 25, bFill = TRUE)
lines(y3$centers, y3$avg, col = "blue")