mwCor {astrochron} | R Documentation |
Calculate moving window correlation coefficient for two stratigraphic series, using a 'dynamic window'. 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.
mwCor(dat,cols=NULL,win=NULL,conv=1,cormethod=1,output=T,pl=1,genplot=T,verbose=T)
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 two variable columns 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 edges of the data set are better preserved. |
cormethod |
Method used for calculation of correlation coefficient (1=Pearson, 2=Spearman, 3=Kendall) |
output |
Output results? (T or F) |
pl |
(1) Plot results at center of window, or (2) create "string of points plot" as in Sageman and Hollander (1999) |
genplot |
Generate summary plots? (T or F) |
verbose |
Verbose output? (T or F) |
B.B. Sageman and D.H. Hollander, 1999, Cross correlation of paleoecological and geochemical proxies: A holistic approach to the study of past global change, in E. Barrera and C.C. Johnson, eds., GSA Special Paper 332, p. 365-384.
# generate example series
ex <- cycles(freqs=c(1/40,1/20),noisevar=.2)
# add second variable
ex[3] <- cycles(freqs=c(1/40,1/20),noisevar=0.2)[2]
# jitter sampling times
ex[1]=ex[1]+rnorm(500,sd=1)
# sort
ex = ex[order(ex[,1],na.last=NA,decreasing=FALSE),]
# run mwCor
mwCor(ex,win=50)