mwStats {astrochron}

'Dynamic window' moving average, median and variance of stratigraphic series

Description

'Dynamic window' moving average, median and variance of stratigraphic series. This routine adjusts the number of data points in the window so it has a constant duration in time or space, for use with unevenly sampled data.

Usage

mwStats(dat,cols=NULL,win=NULL,conv=1,ends=F,CI=0,output=T,genplot=T,verbose=T)

Arguments

dat

Your data frame containing stratigraphic data; any number of columns (variables) are permitted, but the first column should be a location identifier (e.g., depth, height, time).

cols

A vector that identifies the variable column to be extracted (first column automatically extracted).

win

Moving window size in units of space or time.

conv

Convention for window placement: (1) center each window on a stratigraphic level in 'dat' (DEFAULT), (2) start with the smallest location datum in 'dat', (3) start with the largest location datum in 'dat'. For options 2 and 3, the center of the window will not necessarily coincide with a measured stratigraphic level in 'dat', but ends of the data set are better preserved. See options 'ends'.

ends

Assign average values to ends, by averaging data before first window, and averaging data after last window? (T or F; only applicable for conv=1)

CI

What confidence interval should be calculated for the average value (0-100 percent). If set to 0, the confidence interval calculation is skipped.

output

Output results? (T or F)

genplot

Generate summary plots? (T or F)

verbose

Verbose output? (T or F)

Details

If conv=1 is selected, the edges of the record are determined using a smaller window size. A constant value is assigned based on the observed values within the first and last 0.5*win of the record.

Value

A data frame with five or six columns: Center of window, Average, Median, Variance, Number of points in window. If CI>0, the sixth column is the value used to determine the confidence interval (add and subtract it from the average)

Examples

# generate example series from ar1 noise, 5 kyr sampling interval
ex = ar1(npts=1001,dt=5)

# jitter sampling times
ex[1]=ex[1]+rnorm(1001,sd=1)
# sort
ex = ex[order(ex[,1],na.last=NA,decreasing=FALSE),]

# run mwStats
mwStats(ex,win=100)