ccf.series.rwl {dplR} | R Documentation |
Computes cross correlations between a tree-ring series and a master chronology built from a rwl object at user-specified lags and segments.
ccf.series.rwl(rwl,series, series.yrs=as.numeric(names(series)), seg.length=50,bin.floor=100,n=NULL, prewhiten = TRUE, biweight=TRUE, pcrit=0.05, lag.max=5, make.plot = TRUE,...)
rwl |
a data.frame with series as columns and years as rows
such as that produced by read.rwl . |
series |
a numeric vector. Usually a tree-ring series. |
series.yrs |
a numeric vector giving the years of series .
Defaults to as.numeric(names(series)) . |
seg.length |
an even integer giving length of segments in years
(e.g., 20, 50, 100 years). |
bin.floor |
a positive integer giving the base for locating
the first segment (e.g.,.1600, 1700, 1800 AD). Typically 0, 10, 50, 100,
etc. |
n |
NULL or an integer giving the filter length for the
hanning filter used for removal of low frequency
variation. |
biweight |
logical flag. If TRUE then a robust mean is calculated
using tbrm . |
prewhiten |
logical flag. If TRUE each series is whitened using
ar . |
pcrit |
a number between 0 and 1 giving the probability for confidence
interval for the ccf . |
lag.max |
an integer giving the maximum lag at which to calculate
the ccf . |
make.plot |
logical flag indicating whether to make a plot. |
... |
other arguments passed to xyplot . |
This function calculates the cross-correlation function between a tree-ring
series and a master chronology built from a rwl object. The cross-correlation
function is done for each segment of the series where segments are lagged by
half the segment length (e.g., 100-year segments would be overlapped by
50-years). The first segment is placed according to bin.floor
. Cross
correlations are calculcated for the first segment, then the
second segment and so on. Correlations are only calculated for segments with
complete overlap with the master chronology.
Each series (inlcuding those in the rwl object) is optionally detrended as the residuals
from a hanning
filter with weight n
. The filter is not applied
if n
is NULL
. Detrending can also be done via prewhitening where
the residuals of an ar
model are added to each series
mean. This is the default. The master chronology is computed as the mean of
rwl object using tbrm
if biweight=TRUE
and rowMeans
if not. Note that detrending can change the length of the series. E.g., a
hanning
filter will shorten the series on either end by
floor(n/2)
. The effects of detrending can be seen with
series.rwl.plot
. The function is typically invoked to produce a
plot.
A list
containing matrices ccf
and bins
. Matrix ccf
contains the correlations between the series and the master chronology at
the lags window given by lag.max
. Matrix bins
contains the
years encapsulated by each bin.
Andy Bunn
corr.rwl.seg
, corr.series.seg
,
skel.plot
, series.rwl.plot
data(co021) dat=co021 #create a missing ring by deleting a year of growth in a random series flagged=dat$'641143' flagged=c(NA,flagged[-325]) names(flagged)=rownames(dat) dat$'641143'=NULL ccf.100=ccf.series.rwl(rwl=dat,series=flagged,seg.length=100)