dplR (version 1.2.4)

corr.series.seg: Compute Correlation between a Series and a Master Chronology

Description

Compute correlation between a tree-ring series and a master chronology by segment.

Usage

corr.series.seg(rwl,series,series.yrs=as.numeric(names(series)),
  seg.length=50,bin.floor=100,n=NULL, prewhiten = TRUE, biweight=TRUE,
  pcrit=0.05, make.plot = TRUE,...)

Arguments

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.

prewhiten

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

biweight

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

pcrit

a number between 0 and 1 giving the probability for confidence interval for the ccf.

make.plot

logical flag indicating whether to make a plot.

...

other arguments passed to plot.

Value

• A list containing matrices bins, moving.rho, and vectors spearman.rho, p.val, and overall.

Details

This function calculates the correlation a tree-ring series and a master chronology built from a rwl object. Correlations are 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. 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. A moving correlation with length equal to the segment length is also calculated between the series and the master. 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.

See Also

corr.series.seg skel.plot series.rwl.plot ccf.series.rwl

Examples

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
  seg.100=corr.series.seg(rwl=dat,series=flagged,seg.length=100,biweight=FALSE)