This function calculates the correlation between a series and a master chronology.
Can be either
This function calculates correlation serially between each tree-ring
series and a master chronology built from all the other series in the
rwl object (leave-one-out principle).
Each series in the rwl object is optionally
detrended as the residuals from a
hanning filter with
n. The filter is not applied if
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 the
rwl object using
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 prewhitening default will change the
series length based on the
ar model fit. The effects of
detrending can be seen with
This function produces the same output of the
overall portion of
corr.rwl.seg. The mean correlation value given is sometimes
referred to as the “overall interseries correlation” or the “COFECHA
interseries correlation”. This output differs from the
statistics given by
rwi.stats in that
the average pairwise correlation between series where this is the
correlation between a series and a master chronology.
data.frame with correlation values and p-values given from
Andy Bunn, patched and improved by Mikko Korpela
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library(utils) data(gp.rwl) foo <- interseries.cor(gp.rwl) # compare to: # corr.rwl.seg(rwl=gp.rwl,make.plot=FALSE)$overall # using pearson's r foo <- interseries.cor(gp.rwl,method="pearson") # two measures of interseries correlation # compare interseries.cor to rbar from rwi.stats gp.ids <- read.ids(gp.rwl, stc = c(0, 2, 1)) bar <- rwi.stats(gp.rwl, gp.ids, prewhiten=TRUE) bar$rbar.eff mean(foo[,1])
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