corr.series.seg {dplR} | R Documentation |
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,
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 non-negative 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 tree-ring 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 p-value for a moving average equal to
seg.length
. Vector spearman.rho
contains
the correlations by bin and p.val
contains
the p-values. Vector overall
contains the average
correlation and p-value.
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)