corr.series.seg {dplR}  R Documentation 
Compute Correlation between a Series and a Master Chronology
Description
Compute correlation between a treering 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,
method = c("spearman", "pearson","kendall"),
pcrit = 0.05,
make.plot = TRUE, floor.plus1 = FALSE, ...)
Arguments
rwl 
a 
series 
a 
series.yrs 
a 
seg.length 
an even integral value giving length of segments in years (e.g., 20, 50, 100 years). 
bin.floor 
a nonnegative integral value giving the base for locating the first segment (e.g., 1600, 1700, 1800 AD). Typically 0, 10, 50, 100, etc. 
n 

prewhiten 

biweight 

method 
Can be either 
pcrit 
a number between 0 and 1 giving the critical value for the correlation test. 
make.plot 

floor.plus1 

... 
other arguments passed to plot. 
Details
This function calculates the correlation between a treering series and a
master chronology built from a rwl object. Correlations are done by
segment (see below) and with a moving correlation with length equal to
the seg.length
. The function is typically invoked to
produce a plot.
Value
A list
containing matrices bins
,
moving.rho
, and vectors spearman.rho
,
p.val
, and overall
.
Matrix bins
contains the years encapsulated by each bin
(segments). Matrix moving.rho
contains the moving
correlation and pvalue for a moving average equal to
seg.length
. Vector spearman.rho
contains
the correlations by bin and p.val
contains
the pvalues. Vector overall
contains the average
correlation and pvalue.
Author(s)
Andy Bunn. Patched and improved by Mikko Korpela.
See Also
corr.series.seg
, skel.plot
,
series.rwl.plot
, ccf.series.rwl
Examples
library(utils)
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)
## Not run:
flagged2 < co021$"641143"
names(flagged2) < rownames(dat)
seg.100.1 < corr.series.seg(rwl=dat, seg.length=100, biweight=FALSE,
series = flagged2)
## Select series by name or column position
seg.100.2 < corr.series.seg(rwl=co021, seg.length=100, biweight=FALSE,
series = "641143")
seg.100.3 < corr.series.seg(rwl=co021, seg.length=100, biweight=FALSE,
series = which(colnames(co021) == "641143"))
identical(seg.100.1, seg.100.2) # TRUE
identical(seg.100.2, seg.100.3) # TRUE
## End(Not run)