interseries.cor: Individual Series Correlation Against a Master Chronology

Description

This function calculates the correlation between a series and a master chronology.

Usage

interseries.cor(rwl,n=NULL,prewhiten=TRUE,biweight=TRUE,
    method = c("spearman", "pearson", "kendall"))

Arguments

rwl

a data.frame with series as columns and years as rows such as that produced by read.rwl.

NULL or an integral value giving the filter length for the hanning filter used for removal of low frequency variation.

prewhiten

logical flag. If TRUE each series is whitened using ar.

biweight

logical flag. If TRUE then a robust mean is calculated using tbrm.

method

Can be either "pearson", "kendall", or "spearman" which indicates the correlation coefficient to be used. Defaults to "spearman". See cor.test.

Value

a data.frame with correlation values and p-values given from cor.test

Details

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 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 the rwl object using tbrm if biweight is 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 prewhitening default will change the series length based on the ar model fit. The effects of detrending can be seen with series.rwl.plot.

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 rbar statistics given by rwi.stats in that rbar is the average pairwise correlation between series where this is the correlation between a series and a master chronology.

Examples

Run this code

# NOT RUN {
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])

# }